From ad8dee002e78a45210c3e2df8a954ffee59cc487 Mon Sep 17 00:00:00 2001 From: Ronan Collobert Date: Fri, 25 Oct 2013 17:16:18 +0200 Subject: [PATCH] added torch3 legacy --- index.html | 7 + torch3/ChangeLog | 149 ++++ torch3/archives/Torch3doc.tgz | Bin 0 -> 1720363 bytes torch3/archives/Torch3src.tgz | Bin 0 -> 789584 bytes torch3/archives/Torch3win.tgz | Bin 0 -> 782984 bytes torch3/credits.html | 65 ++ torch3/documentation.html | 76 ++ torch3/downloads.html | 225 ++++++ torch3/downloads_old.html | 189 +++++ torch3/extras/epc/archives/README_epc | 93 +++ torch3/extras/epc/archives/README_example | 14 + torch3/extras/epc/archives/README_qtplot | 36 + torch3/extras/epc/archives/epc.tar.gz | Bin 0 -> 4905 bytes torch3/extras/epc/archives/epc.tar.gz_old | Bin 0 -> 9869 bytes torch3/extras/epc/archives/epc/LICENSE | 28 + torch3/extras/epc/archives/epc/Makefile | 42 + torch3/extras/epc/archives/epc/epc_utils.cc | 727 ++++++++++++++++++ torch3/extras/epc/archives/epc/epc_utils.h | 56 ++ 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torch3/matos/w_install.pdf create mode 100644 torch3/packages/Torch3.tgz create mode 100644 torch3/packages/convolutions.tgz create mode 100644 torch3/packages/datasets.tgz create mode 100644 torch3/packages/decoder.tgz create mode 100644 torch3/packages/distributions.tgz create mode 100644 torch3/packages/examples.tgz create mode 100644 torch3/packages/gradients.tgz create mode 100644 torch3/packages/kernels.tgz create mode 100644 torch3/packages/matrix.tgz create mode 100644 torch3/packages/nonparametrics.tgz create mode 100644 torch3/packages/speech.tgz create mode 100644 torch3/torch.css diff --git a/index.html b/index.html index d77ab8b..882a33b 100644 --- a/index.html +++ b/index.html @@ -315,6 +315,13 @@

and MacOS X. Core packages also work on Windows.

+

+Legacy +

+ +

+The very old Torch3 version is still available here, should you need it. + diff --git a/torch3/ChangeLog b/torch3/ChangeLog new file mode 100644 index 0000000..eaff04f --- /dev/null +++ b/torch3/ChangeLog @@ -0,0 +1,149 @@ +=============================================================================== + Torch 3.1 +=============================================================================== + +core +==== + * Bagging.cc + - Initialize "is_selected_examples" to NULL. + + * ClassFormatDataSet.cc + - Convert all the frames of targets, and not only the + first one. + + * ClassMeasurer.cc + - Scan all the frames of inputs to compute classification + error, and not only the first one. + - The confusion matrix computation option at the end of + the training as been removed. The confusion matrix is still + available at each iteration. + + * CmdOption.cc + - When calling loadXFile(), a string not always allocated + was freed. + + * DiskDataSet.cc + - The number of examples was computed using io_inputs, even + if it was NULL. + + * KFold.cc + - The size of the folds is more balanced for small folds. + + * MemoryDataSet.cc + - The number of examples was computed using io_inputs, even + if it was NULL. + + * MemoryXFile.cc + - The EOF flag was not updated when reaching the end of file + while reading with the scanf method. + + * MultiClassFormat.cc + - Serious bug when auto-detecting classes corrected. + + * Random.cc + - Using now memmove instead of memcopy (possibility of + overlapping source and destination). + +matrix +====== + * Mat.cc and Mat.h + - Initializing a matrix from a "real *" now possible. + +gradients +========= + + * SumMachine.cc + - The gradient is now well back-propagated. + +kernels +======= + * QCTrainer.cc + - Bug when updating alpha corrected. Note: very rare + case in practice. Thanks to Stephen Schiller for the + report of this tricky bug. + +distributions +============= + * DiagonalGMM.cc + - log_probabilities are now correctely computed for the viterbi case + - frameExpectation becomes frameDecision + - keep the best gaussian for the current frame + + * Distribution.cc + - resize the output of the machine correctely + - added decision and frameDecision method + + * HMM.cc + - added states shared parameters + + * MAPDiagonalGMM.cc + - adapt the parameters only if the gaussian have "seen" at + least one frame + + * Multinomial.cc + - added equal initialization option + - added check that the log weights are number + - frameExpectation becomes frameDecision + + * NLLCriterion.cc + - correct the beta and outputs resize + + * ParzenDistribution.cc + - correct the resize of the log_probablities + - added frameExpectation method + + * TableLookupDistribution.cc + - correction of some bugs to calculate the log probablity + + * ViterbiTrainer.cc ,ViterbiTrainer.h + - this class is suppressed, it was already included in EMTrainer + + +datasets +======== + + * IOHTK.cc + - correction of some major bugs when reading the HTK files on + disk on unsequential mode + - correction of major bug on double mode + + * IOHTKTarget.cc + - space followed by tabulation allowed instead of space only + - added some check + + * IOHTKTarget.h + - make saveSequence static + + * Vocabulary.cc + - bound check corrected for the number of words + +speech +====== + + * EditDistance.{cc,h} and EditDistanceMeasurer.{cc,h} + - Add a constructor option to print a confusion matrix as well + + * WordSeg.{cc,h} and FrameSeg.{cc,h} + - Two new class to keep the word and frame segmentations found + by viterbi decoding. These are kept separate so as to be + compatible with any new subclass of SpeechHMM. + + * WordSegMeasurer.{cc,h} and FrameSegMeasurer.{cc,h} + - Measurers that outputs information related to the number + of errors in terms of word error rate (WordSegMeasurer) or + frame error rate (FrameSegMeasurer), using the EditDistance + class to compute the error. + + * SimpleDecoderSpeechHMM.{cc,h} + - Modifications to take into account the new WordSeg and FrameSeg + classes + - added a structure (previous_states[] and n_previous_states) + to speedup the decoding process by only looping on existing + transitions and not all possible transitions + - Added an option to be able to decode using "forced alignment", + hence instead of decoding on the whole grammar, decoding on + a given (true) sentence + + * SpeechHMM.cc + - bug corrections related to initialization + diff --git a/torch3/archives/Torch3doc.tgz b/torch3/archives/Torch3doc.tgz new file mode 100644 index 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Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+

+ +

Authors

+ +
+ +

Contributors

+ +
+ +

Cool Stuff

+
    +
  • phpBB team for its very nice GPL'ed forum toolkit. Powered by phpBB2
  • +
  • Julian Seward for his memory debugger tool, Valgrind. + Without it, Torch3 wouldn't have been developped so fast!
  • +
+
+ +

Special

+ +
+ + + diff --git a/torch3/documentation.html b/torch3/documentation.html new file mode 100644 index 0000000..61594b5 --- /dev/null +++ b/torch3/documentation.html @@ -0,0 +1,76 @@ + + + + + + Torch3' Documentation + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +

Disclaimer

+
+Torch3 is not compatible with Torch2. The structure is similar, but a lot of things have been +simplified. There is no script to convert your Torch2 code, but it should be easy to do it. You should use +Torch3 because it's easier to code with it, and because we provide tutorials for a quick start. +
+
+ +

Installation

+
+Torch is pretty easy to install under Unix and Linux systems, including Mac OS X. Before asking questions, +
    +
  • have a look here if you want to use xmake (recommended). +
  • have a look here if you want to use GNU Make. +
+Note that xmake is a fast (and easy) python script designed for compiling Torch. Makefiles are not needed anymore.
+
+ For people using MS Windows, two solutions are possible: +
    +
  • Install Linux using the free Debian distribution which provides more than 8000 useful packages, and +then go here (recommended).
  • +
  • Otherwise, if you really want to keep MS Windows, use instructions provided here. +
+
+
+ +

Tutorials

+
+Several tutorials are provided for the beginner in Torch. + +
+
+ +

One-line documentation

+
+If you are looking for a class, check the class hierarchy.
+If you want to see the documentation for all classes, go there. +
    +
+
+ + diff --git a/torch3/downloads.html b/torch3/downloads.html new file mode 100644 index 0000000..5c00827 --- /dev/null +++ b/torch3/downloads.html @@ -0,0 +1,225 @@ + + + + + + Torch3: The Dream Comes True + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +
+ + + + +
+
+ +Release 3.1 +
+August 11, 2004

+This is a minor update (bug corrections).
See the ChangeLog.


+
+
+ +
+
+ + + + +
+
+ +Torch 3 Vision +

+A full additional package for machine learning applied to vision applications is now available.
+Have a look here.


+
+
+
+ +

Downloads

+
+Please, read the installation notes in the documentation section before downloading anything. +
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + +
Downloads
    Archive    Description
Torch3 srcTorch3 for Unix/Linux
Torch3 docTorch3 documentation
Torch3 win   Torch3 for MS Windows   
+
+
+
+ + + + +
+
+ +Warning! +

+ +We strongly encourage you to use from now xmake (a python script designed for Torch) instead of the GNU make software for compiling Torch. + +
+
+
+ +
+
+Note that the sources for Unix/Linux and MS Windows are the same... only the packaging method +is different.
+If for some reasons you want the previous version of Torch, it is still available here. +
+ +
+ +

Short description of packages

+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Packages
PackageDescriptionDependenciesMaintainers
coreThe core of TorchRonan Collobert
gradientsGradient machinesRonan Collobert
kernelsMachine based on kernel methods,
such as SVM
Ronan Collobert
distributionsStuff related to distributionsgradientsSamy Bengio
Johnny Mariéthoz
convolutionsSpatial and temporal convolutionsgradientsRonan Collobert
matrixMatrix manipulationsRonan Collobert
datasetsSeveral classes to handle data
such as HTK
distributions
speech
Johnny Mariéthoz
 non-parametrics Non-parametrics algorithms,
such as KNN or Parzen Windows
Samy Bengio
speechTools for speech recognitiondistributions
datasets
Samy Bengio
Johnny Mariéthoz
decoderLarge vocabulary speech decoderdistributions
datasets
speech
Darren Moore
examplesSome main program examplesall packages
if you want to run all
all coders
+
+
+ + +
+
+ + + diff --git a/torch3/downloads_old.html b/torch3/downloads_old.html new file mode 100644 index 0000000..9810fec --- /dev/null +++ b/torch3/downloads_old.html @@ -0,0 +1,189 @@ + + + + + + Torch3: The Dream Comes True + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +
+ + + + +
+
+ +Release 3 +
+February 4, 2003 +
+
+
+ +

Downloads

+
+Please, read the installation notes in the documentation section before downloading anything. +
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + +
Downloads
    Archive    Description
Torch3 srcTorch3 for Unix/Linux
Torch3 docTorch3 documentation
Torch3 win   Torch3 for MS Windows   
+
+
+
+Note that the sources for Unix/Linux and MS Windows are the same... only the packaging method +is different. +
+ +
+ +

Short description of packages

+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Packages
PackageDescriptionDependenciesMaintainers
coreThe core of TorchRonan Collobert
gradientsGradient machinesRonan Collobert
kernelsMachine based on kernel methods,
such as SVM
Ronan Collobert
distributionsStuff related to distributionsgradientsSamy Bengio
Johnny Mariéthoz
convolutionsSpatial and temporal convolutionsgradientsRonan Collobert
matrixMatrix manipulationsRonan Collobert
datasetsSeveral classes to handle data
such as HTK
distributions
speech
Johnny Mariéthoz
 non-parametrics Non-parametrics algorithms,
such as KNN or Parzen Windows
Samy Bengio
speechTools for speech recognitiondistributions
datasets
Samy Bengio
Johnny Mariéthoz
decoderLarge vocabulary speech decoderdistributions
datasets
speech
Darren Moore
examplesSome main program examplesall packages
if you want to run all
all coders
+
+
+ + +
+
+ + + diff --git a/torch3/extras/epc/archives/README_epc b/torch3/extras/epc/archives/README_epc new file mode 100644 index 0000000..823ee38 --- /dev/null +++ b/torch3/extras/epc/archives/README_epc @@ -0,0 +1,93 @@ +REQUIREMENTS +------------ +- Torch3 (http://www.torch.ch) + +INSTALL +------ +1) decompress the archive in the Torch3 directory +- cd Torch3;tar zxvf epc.tar.gz +2) add the epc package in the torch packages +- edit Makefile_options_Linux, add epc to packages = +3) compile again +- make depend;make +4) go to epc examples directory +- cd examples/epc +5) compile the programs +- make measure_verif +- make measure_tc + +USAGE +----- +# +# usage: ./Linux_OPT_FLOAT/measure_verif [options] +# + +Arguments: + -> ascii training matrix file () + -> ascii test matrix file () + +Options: + -c -> column where the score is [0] + -s -> step between points for the curves [0.001] + +Curves: + -det_file -> compute FAR/FRR DET curves [] + -roc -> ROC instead of DET + -epc_file -> use the FAR/FRR DCF criterion [] + -criterion -> frr, far, dcf values [dcf] + -bound -> bound for the criterion values [1] + +Points: + -eer_file -> compute EER points [] + -hter_file -> compute HTER points [] + +Stats: + -no_stats -> compute far/frr statistics + + + + The output files (roc, det, epc) for verification is a simple ascii file of + six columns: + + + Install the examples package and run try_it scripts. + + +# +# usage: ./Linux_OPT_FLOAT/measure_tc [options] +# + +Arguments: + -> ascii training matrix file () + -> ascii test matrix file () + +Options: + -c -> column where the score is [0] + -s -> step between points for the curves [0.001] + +Curves: + -F1 -> compute the F1 measure instead of (P+R)/2 + -roc_file -> compute PRECISION/RECALL ROC curves [] + -epc_file -> use the PRECISION/RECALL DCF criterion [] + -criterion -> recall, precision, dcf values [dcf] + -bound -> bound for the criterion values [1] + +Points: + -bep_file -> compute BEP points [] + +Stats: + -no_stats -> compute precision/recall statistics + + + The output files (roc, epc) for text categorization is a simple ascii file of + six columns: + <1/2(train-precision + train-recall)> + <1/2(test-precision + test-recall)> + + with "-F1" option: + <2(train-precision * train-recall)/(train-precision+train-recall> + <2(test-precision * test-recall)/(test-precision+test-recall> + + Install the examples package and run try_it scripts. + + diff --git a/torch3/extras/epc/archives/README_example b/torch3/extras/epc/archives/README_example new file mode 100644 index 0000000..32e8aa5 --- /dev/null +++ b/torch3/extras/epc/archives/README_example @@ -0,0 +1,14 @@ +REQUIREMENTS +------------ +- torch3 (http://www.torch.ch) +- torch3 epc package + +INSTALL +------- +1) uncompress the archive in the Torch3 directory + - cd Torch3; tar zxvf epc_examples.tar.gz +2) go to the directory + - cd examples/epc +3) look at the try_it script and select the ploting program (qtplot or gnuplot) +4) run the script ./try_it + diff --git a/torch3/extras/epc/archives/README_qtplot b/torch3/extras/epc/archives/README_qtplot new file mode 100644 index 0000000..246b287 --- /dev/null +++ b/torch3/extras/epc/archives/README_qtplot @@ -0,0 +1,36 @@ +DESCRIPTION +----------- +This program is written in Qt and can plot curves from data. +Features: + - zooming (right mouse button to zoom, zoom button to reset) + - printing + - measures (left mouse button) + +REQUIREMENTS +------------ +- Torch (http://www.torch.ch) +- Qt library version >= 3.0 (http://www.trolltech.com) +- qwt library version >= 0.4.1 (http://qwt.sourceforge.net) +- qtplot is based in part on the work of the Qwt project (http://qwt.sf.net). + + + +INSTALL +------- +1) Install torch3 library (seed Torch3 documentation http://www.torch.ch) +2) Install epc packages +3) set a new environnement variable TORCHDIR to your Torch3 directory + - export TORCHDIR=/home/marietho/src/Torch3 [for sh shells] + - setenv TORCHDIR /home/marietho/src/Torch3 [for csh shells] +4) uncompress the archive in the examples/epc directory + - tar zxvf qtplot.tar.gz +5) go to qtplot directory + - cd qtplot +6) create the makefile + - qmake qtplot +7) compile the prgram + - make + +USAGE +----- +Run ../Linux_OPT_FLOAT/qtplot. diff --git a/torch3/extras/epc/archives/epc.tar.gz b/torch3/extras/epc/archives/epc.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..3b2b93c9d74d9e40d314ce0c0af916035d93d8fa GIT binary patch literal 4905 zcmV+^6V~h>iwFRy>P|oa1MNNkdfGU){WpFJZQ9wv1PC?+l9FUgz-hfpLN1Wb^t-zs z>wsyz12(lyI^Eem@O_JWjwIVMwnIomXS&5RLu~2j==?sCENjg9X#d%UuX4Fst{)u0 z-?Cb+*70w-TvOOzc0E&|u5wU2C|3YZQIy)jGjgzL!th#nzTpz`%y-=3*u2YxgZk0! z*C6QYUMA@O!uZ9USW|OTeUw4DwQ4m>|4O}5NBx7D)GL)*4dB&UMSVufn<7ZOzH|LQ zC+|(4EIiXChCL<*FlqVb$X~c7@#f~pnph*^%zewTJ*nF#FHgveoOf$Zr(|IpGm{iO zSsHYEtv7AGC)SR}q*Q8<`Ny#=S@vkU7@JTK+S-ug9KOhP`?4gpTEla_qwx+tTGR2! zaK|KH8jWPBd-hjeF>zee7~PUd;YBWJBEvmG41of9|3z+Y_}=2i^T`j;xbQ>Cf%=Io 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zQ%NMR7^QUwJEMR7vnTBNm0$UlU-^|^`ITS!m0$UlU-^|^_qhHC6@TN_0Pp|+p6?+y literal 0 HcmV?d00001 diff --git a/torch3/extras/epc/archives/epc/LICENSE b/torch3/extras/epc/archives/epc/LICENSE new file mode 100644 index 0000000..fd05c81 --- /dev/null +++ b/torch3/extras/epc/archives/epc/LICENSE @@ -0,0 +1,28 @@ + +Copyright (c) 2003 Ronan Collobert +Copyright (c) 2003 Samy Bengio +Copyright (c) 2003 Johnny Mariéthoz + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. +2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. +3. The name of the author may not be used to endorse or promote products + derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR +IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES +OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. +IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, +INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT +NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF +THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/torch3/extras/epc/archives/epc/Makefile b/torch3/extras/epc/archives/epc/Makefile new file mode 100644 index 0000000..1c3355d --- /dev/null +++ b/torch3/extras/epc/archives/epc/Makefile @@ -0,0 +1,42 @@ +# get user and architecture specific options +OS := $(shell uname -s) +TORCHDIR := $(shell cd ..; pwd) +include ../Makefile_options_$(OS) + +CC_FILES := $(wildcard *.cc) +OBJS := $(foreach f,$(CC_FILES),$(OBJS_DIR)/$(patsubst %.cc,%.o,$(f))) + +all: $(LIBTORCH) + +$(LIBTORCH): $(OBJS) + @echo "Archiving..." + @$(AR) $(LIBTORCH) $(OBJS) + +$(OBJS_DIR)/%.o: %.cc + @echo $< + @$(CC) $(CFLAGS_$(MODE)) $(INCS) -o $@ -c $<;sleep 1 + +distclean: + @\rm -f .deps_* + +clean: + @echo "Remove objects file and dependencies..." + @\rm -Rf $(OBJS) $(LIBTORCH) + @\rm -f .deps_$(VERSION_KEY) + +depend: + @echo "Tracking dependencies..." + @\rm -f .deps_$(VERSION_KEY) + @for file in *.cc ; do printf "$(OBJS_DIR)/" >> .deps_$(VERSION_KEY); $(DEP) $(CFLAGS_$(MODE)) $(INCS) $$file >> .deps_$(VERSION_KEY); done + +.deps_$(VERSION_KEY): + @echo ">>> Please do a 'make depend' <<<" + exit 10 + +ifneq ($(MAKECMDGOALS),distclean) +ifneq ($(MAKECMDGOALS),clean) +ifneq ($(MAKECMDGOALS),depend) +include .deps_$(VERSION_KEY) +endif +endif +endif diff --git a/torch3/extras/epc/archives/epc/epc_utils.cc b/torch3/extras/epc/archives/epc/epc_utils.cc new file mode 100644 index 0000000..81ac76c --- /dev/null +++ b/torch3/extras/epc/archives/epc/epc_utils.cc @@ -0,0 +1,727 @@ +#include "epc_utils.h" + +namespace Torch{ + real computeEER(Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_,bool sort){ + + //sort the scores + if(sort) + qsort(to_sort, n, sizeof(Int_real), compar_int_real); + + //find the number of positive and negative targets + int number_of_clients = 0; + if(number_of_clients_ < 0){ + for(int i=0;ithrd_min)){ + if (to_sort[i].the_int){ + n_c++; + }else{ + n_i--; + } + thrd_min = to_sort[i+1].the_real; + i++; + } + *far=n_i/(real)number_of_impostors; + *frr=n_c/(real)number_of_clients; + } + + real computeClassERR(Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_,bool sort){ + + //sort the scores + if(sort) + qsort(to_sort, n, sizeof(Int_real), compar_int_real); + + //find the number of positive and negative targets + int number_of_clients = 0; + if(number_of_clients_ < 0){ + for(int i=0;i v2.real1) + return 1; + if (v1.real1 < v2.real1) + return -1; + return 0; + } + + void sort_scores(Int_real* to_sort, err* e, bool sort) + { + //sort the scores + if(sort) + qsort(to_sort, e->n, sizeof(Int_real), compar_int_real); + + //find the number of positive and negative targets + int n_p = 0; + if(e->n_p < 0) { + for(int i=0;in;i++) + if(to_sort[i].the_int == 1) + n_p++; + e->n_p = n_p; + } + e->n_n = e->n - e->n_p; + } + + real computeSS_DCF(Int_real* to_sort, err* e, real ratio_of_sensitivity, bool sort) + { + real ratio_of_specificity = 1. - ratio_of_sensitivity; + + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + real cost_max = -100; + real cost = cost_max + 1; + real thrd_max = to_sort[0].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real specificity=e->tn/(real)(e->tn + e->fp); + real sensitivity=e->tp/(real)(e->tp + e->fn); + cost = ratio_of_sensitivity * sensitivity + ratio_of_specificity * specificity; + if(cost > cost_max){ + cost_max = cost; + if(i != 0) + thrd_max = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_max = current_thrd; + } + } + return (thrd_max); + } + + real computePR_DCF(Int_real* to_sort, err* e,real ratio_of_precision, bool sort) + { + + sort_scores(to_sort,e,sort); + real ratio_of_recall = 1. - ratio_of_precision; + + e->fp = 0; + e->fn = e->n_p; + real cost_max = -100; + real cost = cost_max + 1; + real thrd_max = to_sort[0].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real current_precision=e->tp/(real)(e->tp + e->fp); + real current_recall=e->tp/(real)(e->tp + e->fn); + cost = ratio_of_precision * current_precision + ratio_of_recall * current_recall; + if(cost > cost_max){ + cost_max = cost; + if(i != 0) + thrd_max = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_max = current_thrd; + } + } + return (thrd_max); + } + + real computeDCF(Int_real* to_sort, err* e,real ratio_of_far, bool sort) + { + sort_scores(to_sort,e,sort); + + real ratio_of_frr = 1. - ratio_of_far; + + e->fp = 0; + e->fn = e->n_p; + real cost_min = 100; + real cost = cost_min - 1; + real thrd_min = to_sort[0].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real current_far=e->fp/(real)(e->fp + e->tn); + real current_frr=e->fn/(real)(e->fn + e->tp); + cost = ratio_of_far * current_far + ratio_of_frr * current_frr; + if(cost < cost_min){ + cost_min = cost; + if(i != 0) + thrd_min = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_min = current_thrd; + } + } + return (thrd_min); + } + + real computeNISTDCF(Int_real* to_sort, err* e,real ratio_of_far, bool sort) + { + sort_scores(to_sort,e,sort); + + //real ratio_of_far = 1. - ratio_of_frr; + real ratio_of_frr = 1.; + + e->fp = 0; + e->fn = e->n_p; + real cost_min = 100; + real cost = cost_min - 1; + real thrd_min = to_sort[0].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real current_far=e->fp/(real)(e->fp + e->tn); + real current_frr=e->fn/(real)(e->fn + e->tp); + cost = ratio_of_far * current_far + ratio_of_frr * current_frr; + if(cost < cost_min){ + cost_min = cost; + if(i != 0) + thrd_min = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_min = current_thrd; + } + } + return (thrd_min); + } + + real computeBEP(Int_real* to_sort, err* e,bool sort) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + real cost_min = 100; + real cost = cost_min - 1; + real thrd_min = to_sort[e->n-1].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real current_precision=e->tp/(real)(e->tp + e->fp); + real current_recall=e->tp/(real)(e->tp + e->fn); + //printf("P %f R %f (P+R)/2 %f \n",current_precision,current_recall,(current_precision+current_recall)/2); + cost = fabs(current_precision-current_recall); + if(cost <= cost_min){ + cost_min = cost; + if(i != 0) + thrd_min = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_min = current_thrd; + } + } + return (thrd_min); + } + + real computeSS_BEP(Int_real* to_sort, err* e,bool sort) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + real cost_min = 100; + real cost = cost_min - 1; + real thrd_min = to_sort[0].the_real; + + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + real current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + real current_specificity=e->tn/(real)(e->tn + e->fp); + real current_sensitivity=e->tp/(real)(e->tp + e->fn); + cost = fabs(current_sensitivity-current_specificity); + if(cost < cost_min){ + cost_min = cost; + if(i != 0) + thrd_min = (current_thrd + to_sort[i-1].the_real)/2.0; + else + thrd_min = current_thrd; + } + } + return (thrd_min); + } + + real computeThGivenSensitivity(Int_real* to_sort, err* e,real given_sensitivity, bool sort) + { + + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_sensitivity = -1; + real previous_specificity = -1; + real previous_thrd = -1; + real current_sensitivity = -1; + real current_specificity = -1; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_specificity=e->tn/(real)(e->tn + e->fp); + current_sensitivity=e->tp/(real)(e->tp + e->fn); + if (current_sensitivity > given_sensitivity) + break; + previous_sensitivity = current_sensitivity; + previous_specificity = current_specificity; + previous_thrd = current_thrd; + } + if (current_sensitivity - given_sensitivity > given_sensitivity - previous_sensitivity) { + current_thrd = previous_thrd; + } + return (current_thrd); + } + + real computeThGivenSpecificity(Int_real* to_sort, err* e,real given_specificity, bool sort) + { + + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_sensitivity = -1; + real previous_specificity = -1; + real previous_thrd = -1; + real current_specificity = -1; + real current_sensitivity = -1; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_specificity=e->tn/(real)(e->tn + e->fp); + current_sensitivity=e->tp/(real)(e->tp + e->fn); + if (current_specificity < given_specificity) + break; + previous_sensitivity = current_sensitivity; + previous_specificity = current_specificity; + previous_thrd = current_thrd; + } + if (given_specificity - current_specificity > previous_specificity - given_specificity) { + current_thrd = previous_thrd; + } + return (current_thrd); + } + + real computeThGivenRecall(Int_real* to_sort, err* e,real given_recall, bool sort) + { + + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_precision = -1; + real previous_recall = -1; + real previous_thrd = -1; + real current_recall = -1; + real current_precision = -1; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_precision = e->tp/(real)(e->tp + e->fp); + current_recall=e->tp/(real)(e->tp + e->fn); + if (current_recall > given_recall) + break; + previous_precision = current_precision; + previous_recall = current_recall; + previous_thrd = current_thrd; + } + if (current_recall - given_recall > given_recall - previous_recall) { + current_thrd = previous_thrd; + } + //printf("given recall %f current_recall %f previous_recall %f current_thresh %f\n",given_recall,current_recall,previous_recall,current_thrd); + return (current_thrd); + } + + real computeThGivenPrecision(Int_real* to_sort, err* e,real given_precision, bool sort) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_precision = -1; + real previous_recall = -1; + real previous_thrd = -1; + real current_precision = 0; + real current_recall = 0; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_precision=e->tp/(real)(e->tp + e->fp); + current_recall=e->tp/(real)(e->tp + e->fn); + if (current_precision < given_precision) + break; + previous_precision = current_precision; + previous_recall = current_recall; + previous_thrd = current_thrd; + } + if (given_precision - current_precision > previous_precision - given_precision) { + current_thrd = previous_thrd; + } + return (current_thrd); + } + + real computeThGivenFAR(Int_real* to_sort, err* e,real given_far, bool sort) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_far = -1; + real previous_frr = -1; + real previous_thrd = -1; + real current_far = 0; + real current_frr = 0; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_far=e->fp/(real)(e->tn + e->fp); + current_frr=e->fn/(real)(e->tp + e->fn); + if (current_far > given_far) + break; + previous_far = current_far; + previous_frr = current_frr; + previous_thrd = current_thrd; + } + if (current_far - given_far > given_far - previous_far) { + current_thrd = previous_thrd; + } + return (current_thrd); + } + + real computeThGivenFRR(Int_real* to_sort, err* e,real given_frr, bool sort) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + + real previous_far = -1; + real previous_frr = -1; + real previous_thrd = -1; + real current_frr = 0; + real current_far = 0; + real current_thrd = -1; + for(int i=e->n-1;i>=0;i--){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + current_thrd = to_sort[i].the_real; + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + current_far=e->fp/(real)(e->tn + e->fp); + current_frr=e->fn/(real)(e->tp + e->fn); + if (current_frr < given_frr) + break; + previous_far = current_far; + previous_frr = current_frr; + previous_thrd = current_thrd; + } + if (given_frr - current_frr > previous_frr - given_frr) { + current_thrd = previous_thrd; + } + return (current_thrd); + } + + void compute4values(real thrd, Int_real* to_sort, err* e,bool sort,bool equal) + { + sort_scores(to_sort,e,sort); + + e->fp = 0; + e->fn = e->n_p; + real thrd_min = to_sort[e->n-1].the_real; + + int i = e->n-1; + while((i >=0 ) && (equal? thrd<=thrd_min : thrdfn == e->n_p)){ + if (to_sort[i].the_int == 1){ + e->fn--; + }else{ + e->fp++; + } + thrd_min = to_sort[i-1].the_real; + i--; + } + e->tp = e->n_p - e->fn; + e->tn = e->n_n - e->fp; + } + + real epcPrecision(real incr,real bound,Int_real* train_scores,Int_real* test_scores,err* etr, err* ete, DiskXFile* f,real_3* prec_scores,bool F1,bool aurocc) + { + real sum = 0; + for (int i=0;in;i++) { + compute4values(train_scores[i].the_real,train_scores,etr,false,false); + //precision + prec_scores[i].real1 = etr->tp/(real)(etr->tp + etr->fp); + //recall + prec_scores[i].real3 = etr->tp/(real)(etr->tp + etr->fn); + prec_scores[i].real2 = train_scores[i].the_real; + } + qsort(prec_scores, etr->n, sizeof(real_real), compar_real_real); + real r = incr; + for (int i=0;in;i++) { + if (prec_scores[i].real1 > r) { + compute4values(prec_scores[i].real2,test_scores,ete,false,false); + real precision = ete->tp/(real)(ete->tp + ete->fp); + real recall = ete->tp/(real)(ete->tp + ete->fn); + if(!aurocc){ + if(!F1) + f->printf("%f %f %f %f %f %f %f\n",prec_scores[i].real1,prec_scores[i].real3,0.5*prec_scores[i].real1+0.5*prec_scores[i].real3,precision,recall,0.5*precision+0.5*recall,r); + else + f->printf("%f %f %f %f %f %f %f\n",prec_scores[i].real1,prec_scores[i].real3,2*prec_scores[i].real1*prec_scores[i].real3/(prec_scores[i].real1+prec_scores[i].real3),precision,recall,2*precision*recall/(precision+recall),r); + } + else sum += recall + precision; + r += incr; + if(prec_scores[i].real1 >= bound) break; + } + } + return sum; + } + + real ppndf(real p) + { + real SPLIT = 0.42; + real A0 = 2.5066282388; + real A1 = -18.6150006252; + real A2 = 41.3911977353; + real A3 = -25.4410604963; + real B1 = -8.4735109309; + real B2 = 23.0833674374; + real B3 = -21.0622410182; + real B4 = 3.1308290983; + real C0 = -2.7871893113; + real C1 = -2.2979647913; + real C2 = 4.8501412713; + real C3 = 2.3212127685; + real D1 = 3.5438892476; + real D2 = 1.6370678189; + + //real eps = 2.2204e-16; + real eps = 2.2204e-7; + real ret_val; + real r; + + if (p >= 1.0) p = 1 - eps; + if (p<= 0.0) p = eps; + real q = p - 0.5; + if (fabs(q) <= SPLIT) { + r = q*q; + ret_val = q * (((A3 * r + A2) * r + A1) * r + A0) /((((B4 * r + B3) * r + B2) * r + B1) * r + 1.0); + } else { + r = q > 0.0 ? 1.0 - p : p; + if (r <= 0) + error("Found r = %f\n",r); + else + r = sqrt( - log(r)); + ret_val = (((C3 * r + C2) * r + C1) * r + C0)/((D2 * r + D1) * r + 1.0); + if (q < 0) + ret_val *= -1.0; + } + return ret_val; + } + +} diff --git a/torch3/extras/epc/archives/epc/epc_utils.h b/torch3/extras/epc/archives/epc/epc_utils.h new file mode 100644 index 0000000..7340852 --- /dev/null +++ b/torch3/extras/epc/archives/epc/epc_utils.h @@ -0,0 +1,56 @@ +#ifndef EPC_UTILS_INC +#define EPC_UTILS_INC + +#include "general.h" +#include "TwoClassFormat.h" +#include "int_real.h" +#include "DiskXFile.h" + +namespace Torch { +struct err { + int fp; + int fn; + int tp; + int tn; + int n_p; + int n_n; + int n; +}; + +struct real_3 { + real real1; + real real2; + real real3; +}; + + //general functions + int compar_real3(const void *p1, const void *p2); + void sort_scores(Int_real* to_sort, err* e, bool sort); + void compute4values(real thrd, Int_real* to_sort, err* e,bool sort,bool equal); + + //precision and recall + real computePR_DCF(Int_real* to_sort, err* e,real ratio_of_precision, bool sort); + real computeThGivenRecall(Int_real* to_sort, err* e,real given_recall, bool sort); + real computeThGivenPrecision(Int_real* to_sort, err* e,real given_precision, bool sort); + real epcPrecision(real incr,real bound,Int_real* train_scores,Int_real* test_scores,err* etr, err* ete, DiskXFile* f,real_3* prec_scores,bool F1,bool aurocc); + real computeBEP(Int_real* to_sort, err* e,bool sort); + + // sensitivity specificity + real computeSS_DCF(Int_real* to_sort, err* e, real ratio_of_sensitivity, bool sort); + real computeSS_BEP(Int_real* to_sort, err* e,bool sort); + real computeThGivenSensitivity(Int_real* to_sort, err* e,real given_sensitivity, bool sort); + real computeThGivenSpecificity(Int_real* to_sort, err* e,real given_specificity, bool sort); + + // far frr + real computeDCF(Int_real* to_sort, err* e,real ratio_of_far, bool sort); + real computeNISTDCF(Int_real* to_sort, err* e,real ratio_of_far, bool sort); + real computeThGivenFAR(Int_real* to_sort, err* e,real given_far, bool sort); + real computeThGivenFRR(Int_real* to_sort, err* e,real given_frr, bool sort); + real ppndf(real p); + real computeEER(Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_ = -1, bool sort=true); + real computeHTER(Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_ = -1, bool sort=true); + void computeFaFr(real thrd, Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_ = -1,bool sort = true); + real computeClassERR(Int_real* to_sort, int n, real* frr, real* far, int number_of_clients_ = -1, bool sort=true); + +} +#endif diff --git a/torch3/extras/epc/archives/epc/int_real.cc b/torch3/extras/epc/archives/epc/int_real.cc new file mode 100644 index 0000000..24c60ff --- /dev/null +++ b/torch3/extras/epc/archives/epc/int_real.cc @@ -0,0 +1,46 @@ +#include "int_real.h" + +namespace Torch { + +extern "C" int compar_int_real(const void *p1, const void *p2) +{ + Int_real v1 = *((Int_real*)p1); + Int_real v2 = *((Int_real*)p2); + if (v1.the_real > v2.the_real) + return 1; + if (v1.the_real < v2.the_real) + return -1; + return 0; +} + +extern "C" int compar_real(const void *p1, const void *p2) +{ + real v1 = *((real*)p1); + real v2 = *((real*)p2); + if (v1 > v2) + return 1; + if (v1 < v2) + return -1; + return 0; +} + +extern "C" int compar_real_real(const void *p1, const void *p2) +{ + real_real v1 = *((real_real*)p1); + real_real v2 = *((real_real*)p2); + if (v1.real1 > v2.real1) + return 1; + if (v1.real1 < v2.real1) + return -1; + return 0; +} + +extern "C" int compar_int_char(const void *p1, const void *p2) +{ + Int_char v1 = *((Int_char*)p1); + Int_char v2 = *((Int_char*)p2); + return (strcmp(v1.the_char, v2.the_char)); +} + +} + diff --git a/torch3/extras/epc/archives/epc/int_real.h b/torch3/extras/epc/archives/epc/int_real.h new file mode 100644 index 0000000..fa554d8 --- /dev/null +++ b/torch3/extras/epc/archives/epc/int_real.h @@ -0,0 +1,46 @@ +#ifndef INT_REAL_INC +#define INT_REAL_INC + +#include "general.h" + +namespace Torch { + +/** This simple structure is used to sort data. + #the_int# contains generally the index of a structured object, + while #the_real# contains the value by which we wish + to sort the objects. + + @author Samy Bengio (bengio@idiap.ch) +*/ + +struct Int_real { + int the_int; + real the_real; +}; + +struct real_real { + real real1; + real real2; + real* p_real; +}; + +struct Int_char { + int the_int; + char *the_char; +}; + +/// this function returns 1 if p1->the_real > p2->the_real +extern "C" int compar_int_real(const void *p1, const void *p2); + +/// this function returns 1 if p1 > p2 +extern "C" int compar_real(const void *p1, const void *p2); + +/// this function returns 1 if p1 > p2 +extern "C" int compar_real_real(const void *p1, const void *p2); + +/// this function returns 1 if p1->the_char > p2->the_char +extern "C" int compar_int_char(const void *p1, const void *p2); + +} + +#endif diff --git a/torch3/extras/epc/archives/epc_examples.tar.gz b/torch3/extras/epc/archives/epc_examples.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..f1211e7f856e3523ac8034ef1f5cf2a919c889c1 GIT binary patch literal 821373 zcmV)4K+3-#iwFQ1tO7s)1MK}t({9_A9tNp>f5pM>SSI$#Sr^c9fE*AZY$HTlaYUu!^jrE*{!M=P=l{>||9}3!_>2F`U;WKr{9pd~5C7&5zyHNQ{j0zEcmLsE z{I~zzKmQm1^*{Y@|Equg7ytH8fBc7k_xFGL7ytfGfB#qi>bGBi`CIwzU;gpWfBcJo z`KN#X`yc=9AO9@>-=F^dALal1MTh8L{HwqE>p%TQ|ML6a{rMmM@Q45WU;oX&`@6sX z+du#I4}bahfAx2N{)7F$fBxHlf&cv%|MD;Y)gS)#zyIy;|MU<4?yvv+55NEE@9=m2 zZ-4$xU-Y+s{SSZm&);wLfBQ54>97Cr*T4N|fBfse`!|35?a%*)KKuOEkAMBIe*5Qt`{zIY z^>6>=@BjX9|Nggs_QyZ}iT>;N^>2e-ga7Tn{rdA?{h5BrfA&x03Hj}B|J85* z zfBg9`^*;YC)9Xj6^?!c;|EKuppZ$~nO}=Rg15|LQOP;=ljz|NGzhKmGof|K=axKc<88+u!~1FaNK9{MUc_!yo?l z|IPpDpZ{0?^q<;0{UQJ3-~Qd-{N>;N+rOg+{2%Bs{nKxMq`&l6|DGPFzv2J)pUa#4 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test matrix file () + +Options: + -c -> column where the score is [0] + -s -> step between points for the curves [0.001] + +Curves: + -det_file -> compute FAR/FRR DET curves [] + -roc -> ROC instead of DET + -epc_file -> use the FAR/FRR DCF criterion [] + -criterion -> frr, far, dcf values [dcf] + -bound -> bound for the criterion values [1] + +Points: + -eer_file -> compute EER points [] + -hter_file -> compute HTER points [] + +Stats: + -no_stats -> compute far/frr statistics + + + + The output files (roc, det, epc) for verification is a simple ascii file of + six columns: + + + Install the examples package and run try_it scripts. + + +# +# usage: ./Linux_OPT_FLOAT/measure_tc [options] +# + +Arguments: + -> ascii training matrix file () + -> ascii test matrix file () + +Options: + -c -> column where the score is [0] + -s -> step between points for the curves [0.001] + +Curves: + -F1 -> compute the F1 measure instead of (P+R)/2 + -roc_file -> compute PRECISION/RECALL ROC curves [] + -epc_file -> use the PRECISION/RECALL DCF criterion [] + -criterion -> recall, precision, dcf values [dcf] + -bound -> bound for the criterion values [1] + +Points: + -bep_file -> compute BEP points [] + +Stats: + -no_stats -> compute precision/recall statistics + + + The output files (roc, epc) for text categorization is a simple ascii file of + six columns: + <1/2(train-precision + train-recall)> + <1/2(test-precision + test-recall)> + + with "-F1" option: + <2(train-precision * train-recall)/(train-precision+train-recall> + <2(test-precision * test-recall)/(test-precision+test-recall> + + Install the examples package and run try_it scripts. + + diff --git a/torch3/extras/epc/archives/examples/epc/measure_tc.cc b/torch3/extras/epc/archives/examples/epc/measure_tc.cc new file mode 100644 index 0000000..d097bcf --- /dev/null +++ b/torch3/extras/epc/archives/examples/epc/measure_tc.cc @@ -0,0 +1,268 @@ +const char *help = "\ +(c) Trebolloc & Co 2001\n\ +\n\ +measure_tc\n"; + +#include "CmdLine.h" +#include "IOAscii.h" +#include "DiskXFile.h" +#include "epc_utils.h" + + +/* NOTATION + n = number of examples (n = n_p + n_n) + n_p = number of positives + n_n = number of negatives + n_fp = number of false positives + n_fn = number of false negatives + n_tp = number of true positives + n_tn = number of true negatives + + n_p_tr = number of positives in the training set + n_p_te = number of positives in the test set +*/ + +using namespace Torch; + +int main(int argc, char **argv) +{ + char *train_filename; + char *test_filename; + int column; + bool dcf_criterion = false; + bool precision_criterion = false; + bool recall_criterion = false; + char* criterion; + bool no_stats; + char* roc_file; + char* epc_file; + bool F1; + char* bep_file; + real bound, step; + + Allocator *allocator = new Allocator; + + CmdLine cmd; + cmd.info(help); + cmd.addText("\nArguments:"); + cmd.addSCmdArg("training score file", &train_filename, "ascii training matrix file"); + cmd.addSCmdArg("test score file", &test_filename, "ascii test matrix file"); + + cmd.addText("\nOptions:"); + cmd.addICmdOption("-c", &column, 0, "column where the score is"); + cmd.addRCmdOption("-s", &step, 1e-3, "step between points for the curves"); + + cmd.addText("\nCurves:"); + cmd.addBCmdOption("-F1", &F1, false, "compute the F1 measure instead of (P+R)/2"); + cmd.addSCmdOption("-roc_file", &roc_file, "", "compute PRECISION/RECALL ROC curves"); + cmd.addSCmdOption("-epc_file", &epc_file, "", "use the PRECISION/RECALL DCF criterion"); + cmd.addSCmdOption("-criterion", &criterion, "dcf", "recall, precision, dcf values"); + cmd.addRCmdOption("-bound", &bound,1.,"bound for the criterion values"); + + cmd.addText("\nPoints:"); + cmd.addSCmdOption("-bep_file", &bep_file, "", "compute BEP points"); + + + cmd.addText("\nStats:"); + cmd.addBCmdOption("-no_stats", &no_stats, false, "compute precision/recall statistics"); + + cmd.read(argc, argv); + + IOAscii train_io(train_filename); + IOAscii test_io(test_filename); + + Sequence train_sequence(1, train_io.frame_size); + Sequence test_sequence(1, test_io.frame_size); + + if(train_io.frame_size<2) + error("train frame size should be greather than 2: %d",train_io.frame_size); + if(test_io.frame_size<2) + error("test frame size should be greather than 2: %d",test_io.frame_size); + if(column > train_io.frame_size - 1 || column > test_io.frame_size - 1) + error("bad column number"); + + Int_real* train_scores = (Int_real*)allocator->alloc(train_io.n_sequences*sizeof(Int_real)); + Int_real* test_scores = (Int_real*)allocator->alloc(test_io.n_sequences*sizeof(Int_real)); + + int n_tr = train_io.n_sequences; + int n_p_tr = 0; + for(int t = 0; t < n_tr; t++) { + train_io.getSequence(t, &train_sequence); + train_scores[t].the_real = train_sequence.frames[0][column]; + int target = (int)train_sequence.frames[0][train_io.frame_size-1]; + if(target == 1) + n_p_tr++; + train_scores[t].the_int = target; + } + qsort(train_scores, n_tr, sizeof(Int_real), compar_int_real); + err etr; + etr.n = n_tr; + etr.n_p = n_p_tr; + etr.n_n = n_tr - n_p_tr; + + int n_te = test_io.n_sequences; + int n_p_te = 0; + for(int t = 0; t < n_te; t++) { + test_io.getSequence(t, &test_sequence); + test_scores[t].the_real = test_sequence.frames[0][column]; + int target = (int)test_sequence.frames[0][test_io.frame_size-1]; + if(target == 1) + n_p_te++; + test_scores[t].the_int = target; + } + qsort(test_scores, n_te, sizeof(Int_real), compar_int_real); + err ete; + ete.n = n_te; + ete.n_p = n_p_te; + ete.n_n = n_te - n_p_te; + + // compute curve + + real train_precision,train_recall; + real test_precision,test_recall; + real th = 0; + if(!strcmp(criterion,"dcf")){ + dcf_criterion = true; + }else + if(!strcmp(criterion,"recall")){ + recall_criterion = true; + }else + if(!strcmp(criterion,"precision")){ + precision_criterion = true; + }else{ + error("Option -criterion set with bad value. Take default value"); + } + + + if(strcmp(epc_file, "")){ + DiskXFile x_epc(epc_file,"w"); + if (dcf_criterion) { + real the_bound = 1.; + if (bound < 0.5) the_bound = bound; + else the_bound = 1-bound; + for (real r = the_bound + step; r < 1 - the_bound; r += step) { + th = computePR_DCF(train_scores,&etr,r,false); + train_precision=etr.tp/(real)(etr.tp + etr.fp); + train_recall=etr.tp/(real)(etr.tp + etr.fn); + compute4values(th,test_scores,&ete,false,true); + test_precision=ete.tp/(real)(ete.tp + ete.fp); + test_recall=ete.tp/(real)(ete.tp + ete.fn); + if(!F1){ + x_epc.printf("%f %f %f %f %f %f %f\n",train_precision,train_recall,0.5*train_precision+0.5*train_recall,test_precision,test_recall,0.5*test_precision+0.5*test_recall,r); + }else{ + x_epc.printf("%f %f %f %f %f %f %f\n",train_precision,train_recall,2*train_precision*train_recall/(train_precision+train_recall),test_precision,test_recall,2*test_precision*test_recall/(test_precision+test_recall),r); + } + } + } else if (precision_criterion) { + real_3* prec_scores = (real_3*)allocator->alloc(n_tr*sizeof(real_3)); + epcPrecision(step,bound,train_scores,test_scores,&etr,&ete,&x_epc,prec_scores,F1,false); + } else if (recall_criterion) { + for (real r = step;ralloc(n_tr*sizeof(real_3)); + real sum = epcPrecision(step,bound,train_scores,test_scores,&etr,&ete,NULL,prec_scores,F1,true); + prior_average_P += sum; + printf("Perf test :(AUROCC + 1/2)/2 test : %f\n", (post_average + 0.5)*0.5); + printf("Perf test : E((P+R)/2|P) : %f\n", prior_average_P*step*0.5); + printf("Perf test : E((P+R)/2|R) : %f\n", prior_average_R); + printf("Perf test : E((P+R)/2|DCF) : %f\n", prior_average_PR_DCF*step*0.5); + } + + delete allocator; + return(0); +} diff --git a/torch3/extras/epc/archives/examples/epc/measure_verif.cc b/torch3/extras/epc/archives/examples/epc/measure_verif.cc new file mode 100644 index 0000000..ee91b15 --- /dev/null +++ b/torch3/extras/epc/archives/examples/epc/measure_verif.cc @@ -0,0 +1,295 @@ +const char *help = "\ +(c) Trebolloc & Co 2001\n\ +\n\ +measure_verif\n"; + +#include "CmdLine.h" +#include "IOAscii.h" +#include "DiskXFile.h" +#include "epc_utils.h" + + +/* NOTATION + n = number of examples (n = n_p + n_n) + n_p = number of positives + n_n = number of negatives + n_fp = number of false positives + n_fn = number of false negatives + n_tp = number of true positives + n_tn = number of true negatives + + n_p_tr = number of positives in the training set + n_p_te = number of positives in the test set +*/ + +using namespace Torch; + +int main(int argc, char **argv) +{ + char *train_filename; + char *test_filename; + int column; + bool dcf_criterion = false; + bool far_criterion = false; + bool frr_criterion = false; + char* criterion; + bool no_stats; + char* det_file; + char* epc_file; + bool roc; + char* eer_file; + char* hter_file; + real bound, step; + + Allocator *allocator = new Allocator; + + CmdLine cmd; + cmd.info(help); + cmd.addText("\nArguments:"); + cmd.addSCmdArg("training score file", &train_filename, "ascii training matrix file"); + cmd.addSCmdArg("test score file", &test_filename, "ascii test matrix file"); + + cmd.addText("\nOptions:"); + cmd.addICmdOption("-c", &column, 0, "column where the score is"); + cmd.addRCmdOption("-s", &step, 1e-3, "step between points for the curves"); + + cmd.addText("\nCurves:"); + cmd.addSCmdOption("-det_file", &det_file, "", "compute FAR/FRR DET curves"); + cmd.addBCmdOption("-roc", &roc, false, "ROC instead of DET"); + cmd.addSCmdOption("-epc_file", &epc_file, "", "use the FAR/FRR DCF criterion"); + cmd.addSCmdOption("-criterion", &criterion, "dcf", "frr, far, dcf values"); + cmd.addRCmdOption("-bound", &bound,1.,"bound for the criterion values"); + + cmd.addText("\nPoints:"); + cmd.addSCmdOption("-eer_file", &eer_file, "", "compute EER points"); + cmd.addSCmdOption("-hter_file", &hter_file, "", "compute HTER points"); + + cmd.addText("\nStats:"); + cmd.addBCmdOption("-no_stats", &no_stats, false, "compute far/frr statistics"); + + cmd.read(argc, argv); + + IOAscii train_io(train_filename); + IOAscii test_io(test_filename); + + Sequence train_sequence(1, train_io.frame_size); + Sequence test_sequence(1, test_io.frame_size); + + if(train_io.frame_size<2) + error("train frame size should be greather than 2: %d",train_io.frame_size); + if(test_io.frame_size<2) + error("test frame size should be greather than 2: %d",test_io.frame_size); + if(column > train_io.frame_size - 1 || column > test_io.frame_size - 1) + error("bad column number"); + + Int_real* train_scores = (Int_real*)allocator->alloc(train_io.n_sequences*sizeof(Int_real)); + Int_real* test_scores = (Int_real*)allocator->alloc(test_io.n_sequences*sizeof(Int_real)); + + int n_tr = train_io.n_sequences; + int n_p_tr = 0; + for(int t = 0; t < n_tr; t++) { + train_io.getSequence(t, &train_sequence); + train_scores[t].the_real = train_sequence.frames[0][column]; + int target = (int)train_sequence.frames[0][train_io.frame_size-1]; + if(target == 1) + n_p_tr++; + train_scores[t].the_int = target; + } + qsort(train_scores, n_tr, sizeof(Int_real), compar_int_real); + err etr; + etr.n = n_tr; + etr.n_p = n_p_tr; + etr.n_n = n_tr - n_p_tr; + + int n_te = test_io.n_sequences; + int n_p_te = 0; + for(int t = 0; t < n_te; t++) { + test_io.getSequence(t, &test_sequence); + test_scores[t].the_real = test_sequence.frames[0][column]; + int target = (int)test_sequence.frames[0][test_io.frame_size-1]; + if(target == 1) + n_p_te++; + test_scores[t].the_int = target; + } + qsort(test_scores, n_te, sizeof(Int_real), compar_int_real); + err ete; + ete.n = n_te; + ete.n_p = n_p_te; + ete.n_n = n_te - n_p_te; + + // compute curve + + real train_far,train_frr; + real test_far,test_frr; + real th = 0; + if(!strcmp(criterion,"dcf")){ + dcf_criterion = true; + }else + if(!strcmp(criterion,"frr")){ + frr_criterion = true; + }else + if(!strcmp(criterion,"far")){ + far_criterion = true; + }else{ + error("Option -criterion set with bad value. Take default value"); + } + + + if(strcmp(epc_file, "")){ + DiskXFile x_epc(epc_file,"w"); + if (dcf_criterion) { + real the_bound = 1.; + if (bound < 0.5) the_bound = bound; + else the_bound = 1-bound; + for (real r = the_bound + step; r < 1 - the_bound; r += step) { + th = computeDCF(train_scores,&etr,r,false); + train_far = etr.fp/(real)(etr.fp + etr.tn); + train_frr = etr.fn/(real)(etr.fn + etr.tp); + compute4values(th,test_scores,&ete,false,true); + test_far = ete.fp/(real)(ete.fp + ete.tn); + test_frr = ete.fn/(real)(ete.fn + ete.tp); + x_epc.printf("%f %f %f %f %f %f %f\n",train_far,train_frr,0.5*train_far+0.5*train_frr,test_far,test_frr,0.5*test_far+0.5*test_frr,r); + } + } else if (far_criterion) { + for (real r = step;r|A?y+cvV#ztX2brBg2{)3T)4ajzWb z9LI55_t=SF-A$V2J}Kx3g2~|D8v@-3P4mt^dFH z#?7( zX&jAWK4Ean8Qe|BzRLr4E8@hDLKY1f_t3=HZ((D|Qg6TRMYBO5S}hht+gozDy`%-9$@>?9QvlEh|I1hs%}t){Bifev-nmdhC&+U%J>{=`XTrc&HB#wMj~y4uE83Th$Z9bE@AKsDjFJ|pG*V3Af7-z ziDEX55+7}pWS4N}qm&cm^G6g-Z~)4t{B_0FwH+hj6YyJB<5#%rgED zefi6A8SqOYl8lE!EDKHE=w7J_RTi5v8%qc!I8AXm$uqzT$rML|fI*2Aj0XI->LHR( z-D}y9@^%Y+7Q6WAX*6do4?F|jsODg1z9BWH0FnpH6kxShwd&CE=)3#nZvG5etdCwYSDyuG)Cb(OHQD+?J&|E zjS)bezPz?THmqkL_C8=(Yr9_4ly#RI(k{$@?|~}PBN}8OmQCH5tA!S9Dy3xRo`qh+ zRKzi%a`JVJfU+tk&d`^gMYljfO{bJ|d<&z01L)!GCuJ#uSrz(Ic##XO;>N1kY5YIU z@KOYVe-1}eVHL}IjRKu0PQaYIk4OfUvM!GBwq?Uyi@}nWKr|5zRkq#I6^V+xebaf% z4r1XMGH<$&F^YuJ1342u0x@}(xeJ*K0ixVxd5<8^dRO^GyfqMxYw zLuP3}+fR-s({uq5qFtx(QWwMmVjhUBt&2-BI-XCNp7s0vVH{0PVObS+nbm+*7mm|3 zhI@?m8ZySz3m)_vN)}6z#&T#^9&!Xr1n{_417~|3@X<_@1HFWmB6I_WU6yWpzkdn= zPvY{aD51$h&wyMGE3FpwggVH9XH#%X*m$KZsbvLlSRsP9D|*E^C>Dj(H%K3ErAl>l zgHsj^9a6Bwixl~#?Kd!`1qA>&ZZ2KNSNq*$UY17jE<2M3IiB4xy6=XH_B zJu-x> z);z#3 zVrDow>wGy&13wg3=|UQ3zkdnSB845wlGcKc;wVYhHhJAdnzcCs#|3JPQ+Jjo*ul7p z3=UXX{d|t=hSG?`>_IM9b@5WWwI7JWzolS%w<5+x@q#5dG81+;_T4e#u!J?m!h+SkaQLh|`N$VHjvB9C0;k!6|{NZGc)pZF|VW`PKne zqHPYSv1wA^bZa?kbEF2!+hpr0&I=UhMT)X%SFrRQ`g3TN?5|}nD?KdO4F%RK1~e8! z^BlIiv}afOa7{g4Pd#2sJ-(0nU_JGLGhag;N=wwU8D-_1aL)+8j(u3Q$lZXdNeQ~g z4Eq1oI~VqcIu?AnokE;Ma3_<2Eg4!Uq7I|(5{Q|8OExLG8MdRT2(6Qs?=A)RUWUO! zE&*mKd;B<)1*_u%`iizv+3#s$Z48NMw!woNT<=gtpoAB{oSsU5JoH14_N~I%WB{Qe zj55S1PZm;zLHV5qg-jxe0kTTDPRTxrw?1rwf)=VExo>4Nl9C3Ii`R#!ayCk|I2*nRsXTX?faXX z=+TJs8~<&NxLrY-1TWH-j$DUX4IDP$@4ok>unBf~*vB-oYdDIAqk3w!sh6dtY9#I_ zDfx4ahpgv@?EPP3H_pxGCfE*56;iu5Z${? z?xI^5Qa7s^6QrMbZ47%Y1nKA$<|NS81XhI- zfZJ=}S8)}q*(QCGNR^uAfy31@%FT{qZ3!yYJ;^FJwicju(8h*TzQa188F`P}GAW3K zetehFQh`6t5KIwfDHw|*%!W|YPgb&@EB15Ef2&(5z`R0$t2`mH7Nn&1 z{u@8aC$b53HRj&ncy@3N_!}W*>hvYOLg>&o5=kX^E^TY80^lHB@WIMPUC_i|AwQUPrxL4 z*EYLtkFzlYnKV2K)2W%V<;bBB8e`{_S>Jnh!^udgdG)Sc3f`_s$fYHwRytO@uZ~>b zEV3G9r@hn$8PetEL-d3uR2w=QSvE$iR`>0}jak)D2#aAjn4UG1LHfnH2pLY{cWt#<>A!V)&IQ=WRTTK-qAB$};OP;c z(*09$D}tY4MW=gZZURT-oHIUH0#NT_Z@*EEf9p_6CrnolouN+_gWHL);smK=lqoj` zs>seii&VW#L(bos)`zhWB&r&DyiJcB(Ff2ItBpH3wqk)DV(sp9oSjZb=4pCzI*xCl zUwK>1g-cA-G#}sM4F4Z+{wq5>@&%57tv~&N`yGV}xg>{tPAeWgy})PdcvOxoG3LAH`q@pCr?3=Ue3qU43v2u zC2G@C?c5hipU2>=)K&=Hqt@ns>ier%_`V?0DE2+35|Z_gkn`${RyMSWmCLm#uw2T2 zZSo}@5C*f)_zfxnCkLra3T>Z7DNYCW650<98XtTCm=(}kVmzr+5EvtqiU%56%d2A@ zj4Rgy)dnuak9ldUfND>-aX#jWU~fDzdfUikR+ZFBph6JHF^^mN{nKa!<31fve7DT^ zjL$)>FljH-cvOY;!%8fjb6~pP^}#5aa^qXv1SdGI8uAE_P78F5+*k4!$ z8iBX+39P*YdriHhfaM2O8RuS!v(o5FwmrobpAWBL+H+X7foKhYqkS)8wCfgSP2%^N z63(d5%1lLOoSIEXL=y*D(C`19jJAZwfh&=C)I%QRC=$e@CWnDP3Kfp-N!&l_);xYI z(iIwiVVsT}YCIX2hMTE`2L*L4x^Mg>f?JWo;--Q2p|a6?1fC2QTibQ5o2;9VxYAFf zQPH()8rb{H2I{_+Ck(7!r{i>YL6P<+H@5ewjV;u^T1*B}pz2dl46Rg|=C0p==JQE} z%S|~19Hu(rf{t14IeWHU@CbBfMp}V>5|zz#CODPRI%~}xrf(Mx5uqiNV;+CL7mF;R zSH3zh*Rx*`;f^rHmHANyb+bknN6zXlCEO*KViFQ$1Q}$!tpU@LHgMd%>k)I*J{vs^|J)nh0Mz)EGrNH>?V`u!IX z-N@A#t{*<+t0)KLFvA>IY}vDmiawR+5zV1TItyT_yV_rxBUV>eQ`p+dAHVi;qWJ#D z_{+Tivp)Xsc00S}_dj}%zPqrRh4zpGwAP{-@#LCk%X(xb|pzSo;<+0py# zJh5_q7w=v^{rULlx?ax?;HyJyOm183o1H10#(J6;YsqCl@TC0vk31jX#8f`@Ou5<# z9ONVC>`^4Jn8yAs9+yafV~=%tMzR@@n)2gBO?tckBN$p5VPIwM>P^2)xCB5=9x!Ue^D zrzcb6-<<~YFBJXVJN{wy_^34gAMSO#-^Tyf8UMr36GQg&<+I~=N9U)n-u+Z>LIysr z&*$ahLA^<=y#(40`;d(-^{kA=!oeeW#yjK+c!2L%>W3&||D!4MCw!DE0|NM{3t3q5 z07pzwTbmAt_!9<+Et%4|4Hix10g(e{k!(Cylec4`s$xQ(5md}t_zqc)lJ-ckaY(-8 zoud~UV!o<5!~^i2)QXmbwUj7xa5nO$M<*((u$!NO-TDmdb|seHEA>MplJ z&~1_F?poH{)vT4-cp{`@kA_&!=q=;EUzC)UWZf*vYO`&kN)x1&E7E$CX(WLsX9+9C zuQ$Oo{9!$ReT#$t%j19ZL4kk6{J-0KRDS-uv-9xV^WU#J|DT_{Iy*eS%FX^+P95Lk zf#^TKePZ4te)IO=L%s2^$KYQV{xzI>gEN;khjd|btdpG%Cf#D`5R;yZKbRa~((T|6 zCT}pwJMgoENrA~9I{1Uhkxoj=9wv8xz#mNdnCx^k-=<7<6u1q^7f~qa{+{cfz%-l9 z`!G#D7%amIm?j6zU

lcpk5SOD=vSialni~K!sVNf)M1BVVamZEKwN@#$%|YFjBn=mZw4xg&`gimO*@9 zLJVe*gB7V5%*`MN8x$c11DAo7AO-_Pc~~A&k|z%{kY#xcEQ7QwrgQ_f30gPs6jH*b+rD4pQd0r(NlGj=cUyB(C5JC);SE97<3XW`G6MY6J}`G2pahi(K@uq7u_=nuZh2RT!z^dojdp6$a(em{sx&a?F|t zC}FU+*KFoA&i>A(->ZPHOZr7j(vrDf&b(r)x!1L zqU~S5{<}Ore0FyH@7e!_`||f6AMU`C@Z0+DD_qZxuZ}KH&aY2izNqIvW>)^F<6Z2h zsh}^9UC3|2xm8v zyKB?O5Zmt9hSCdsiG2|Bcws(S`Q(5-YC~ zadmxoda9dU@7nAHVo4qZj2imT2x=t)*j>v^FLLRHI{6+|rFME5B{6kDNcTM-iKPC} z#z$<7)5o<$c(7mkPgAQz15)XN9l=#siPukhsah+m0=~VT8;r*b+H9qNlUi>EZTC4+v zKS}yZ<;hm77axnO`%5hV4*zjGQ`Kj^g{`RtpV;kq~t54#G z23_TBZ57_fO5|!yrd5GBY|w=B>7-SX#6MEr-{P45al?Bxnek@HcVu}l zfJ=zP$i6D0F5-1Y?RF=aW$XL%Xk^cOK_u;FahLe|`Y&{{@3H>t@Y(zS!*})j|8GJt zo>Obyj91rmL@!SZE@qi9Q4)K~?Cl@XQ+8sywGRs@({Uj|HdXf-U4M%~rYVT+a&+MLgQP|V{(oMLNd7~@cjhESZ&Tl~7a5d@i_^vnA%PwpQ{k{ZW(-rn);OKcI1M@w{3cB^1A3sZ5-__f7>pRU za+0E=Np~}hRKRiko3B@5kxyrrRUQCN004-TE*Csm;gzuY?Tk~Ptgfrn6PIk%olC}( zXH%CVtq@#kk*?m0H*MP0s9*$MsWRcDhYNHU7{G}bO1yZH-*Qpq0bW;@<*V5wZ4xgg zDN|~=?dBV4&ZJ#cAaODu&lc&jE#5v?0iw2Cuu%cFP1lq3ztEyWzue63^Z=DQoEZd# zOTf=n3Y0%Dp4{wW!>w)`&=v=6ve#v*k$5mely6Ydf`bL5Uv&0Jl#C<>>Mumf$# zL_K>VV?{U~#nG|$l~3I>vI9jjv4be4j~}H$@ynMaLm%HWQm3O>8ADMlG{$$0Drh5? zq1DPXsT_iJ*l$udu@puYpkk;k*lg5vO+T+Dq8<$uMq-@Gt`4+4bMkuHhAgWGO(czE zY_*pJGNw@yk0Jvtp*(Pm7f3x+ej5M)5=k9n0!(HAz_V>jm+_742C8fiwqW1~ieja! zBSsML0<;L4WJb!mt#pFX1RR25wk0vzxkiUp#c|^Pz-Z7Q zI)U-fQKG8vd>DmnDgv&e_>3E6A2=5`>13dAJw_vJm5n7k!`N7RcAE|IfRn6vvXMg7 z4|HFJp5oGoTRG82H4qVPm_a+Sh%sa)&SZ`Rw8G(T?`yhvk?xW7k2R}ZF(bl8SG~cx p%o|khZrAv!rkZN1sivB0s;Q=$YO1NGnriy@^fy{+@y`Hw008qJ%i{n5 literal 0 HcmV?d00001 diff --git a/torch3/extras/epc/epc.html b/torch3/extras/epc/epc.html new file mode 100644 index 0000000..0913d90 --- /dev/null +++ b/torch3/extras/epc/epc.html @@ -0,0 +1,103 @@ + + + + + + Torch3: The Dream Comes True + + + + + + +

Expected Performance Curves

+ +

Description

+In several research domains concerned with classification tasks, +including person authentication and text categorization, ROC curves +are often used to assess the quality of a particular model or to compare two +or more models. Researchers also often publish some statistics coming +from the ROC curve, such as so-called break-even point or equal +error rate. The purpose of this paper is to argue that these measures +can be misleading and should be avoided. Furthermore, we propose +a replacement for them, called Expected Performance Curves (EPC) +which enable the comparison of several systems according to a criterion, +decided by the application, which is used to set thresholds according to a +separate validation set. + +

Related technical report

+ +S. Bengio, M. Keller, and J. Mariéthoz. + The expected performance curve. + Technical Report IDIAP-RR 03-85, IDIAP, 2003. Submitted for publication. +
[ +
.pdf | +.djvu | +.ps.gz ] + +

+ +

Software

+This software is under the same license as Torch, hence under a BSD license. +
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Dowloads
    Archive    DescriptionDocumentation
Torch3 EPC packageTorch3 EPC package: can compute EPC curvesreadme epc
EPC examplesEPC biometric verification example using gnuplotreadme examples
qtplot   Plotting program written in Qt   readme qtplot
+
+

Example of EPC curve

+
+ + + + + + + + + + + + + + + + + +
Figure Examples
gnuplotqtplot
Figure generated by gnuplotFigure generated by qtplot (zoom)
+
+ +

Authors

+Samy Bengio, Mikaela Keller, Johnny Mariéthoz + + diff --git a/torch3/extras/epc/images/gnuplot.jpg b/torch3/extras/epc/images/gnuplot.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c7836cfc174d0e2adcb61c96241c2c5c8daa6121 GIT binary patch literal 16612 zcmb_@1yodB*Z&|bElLeNgi1++Lx_@!pdd&K49(EeB_N@|P|{rjk^>AK(w))_-7vIt z{pWd~eDnL>Z~bT1x@*t5=bp3oKKt(YoijHRH}e3}=dud201ONafIRvOxVZ)hF)COY zm>M&h8e1FN8@x9*Vl;GRlv7e;lryt&c<%tQH@AJyc;Cp_$sA%VZfk30Z{Ymk_RTcl z82}Fl2Nwq$4;L2~A0O{F;aws^0s=znJLDvH>1Y_}>1b$a8Ckg58JRgjw6ynyA86k^;S=NL7vTG45Da{Ld_n?3Dk35(J| zuwQ2R9(qu!UuOHueCT;GFtKi-?>r(y508O?g^!7a`5QkNx5zNjb4g*5zg97@i)b3+ z^MPZ7()XC3HZR;v0SM9k&^^cil7QXypbtSoctIb67d17pcw(M4w+mFao?!Imo*uPj zhJQ6_K6bJEQE|JP1b?pFAqkTN7ngCn2{$;^obab8!3O5VLN+%>^N`U^6Hjb>FSdghxjsXR4GgBIkdMX6EY3 zkjhzDhKb@(3nZhm?yj0GhKAa?axN~0X3vWdohnlxFT&I!(s{?=r#(Ax%_GAy*B@iw zZU9zTG9eg&gU*&=s^j1Cq)BHxC4eS7m_RKgBE8bo*I63p!tRmd4IsB5?mYv9$`rN> zwm$GW+Q=85`{Dig;`O)IJ6_Tr4$k8zIS~xBGe=jOa8iXcvi-ifce8aUv&z!)qA=d~ 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b/torch3/extras/epc/index.html new file mode 100644 index 0000000..0913d90 --- /dev/null +++ b/torch3/extras/epc/index.html @@ -0,0 +1,103 @@ + + + + + + Torch3: The Dream Comes True + + + + + + +

Expected Performance Curves

+ +

Description

+In several research domains concerned with classification tasks, +including person authentication and text categorization, ROC curves +are often used to assess the quality of a particular model or to compare two +or more models. Researchers also often publish some statistics coming +from the ROC curve, such as so-called break-even point or equal +error rate. The purpose of this paper is to argue that these measures +can be misleading and should be avoided. Furthermore, we propose +a replacement for them, called Expected Performance Curves (EPC) +which enable the comparison of several systems according to a criterion, +decided by the application, which is used to set thresholds according to a +separate validation set. + +

Related technical report

+ +S. Bengio, M. Keller, and J. Mariéthoz. + The expected performance curve. + Technical Report IDIAP-RR 03-85, IDIAP, 2003. Submitted for publication. +
[ +.pdf | +.djvu | +.ps.gz ] + +

+ +

Software

+This software is under the same license as Torch, hence under a BSD license. +
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Dowloads
    Archive    DescriptionDocumentation
Torch3 EPC packageTorch3 EPC package: can compute EPC curvesreadme epc
EPC examplesEPC biometric verification example using gnuplotreadme examples
qtplot   Plotting program written in Qt   readme qtplot
+
+

Example of EPC curve

+
+ + + + + + + + + + + + + + + + + +
Figure Examples
gnuplotqtplot
Figure generated by gnuplotFigure generated by qtplot (zoom)
+
+ +

Authors

+Samy Bengio, Mikaela Keller, Johnny Mariéthoz + + diff --git a/torch3/extras/epc/publications/rr03-84.djvu b/torch3/extras/epc/publications/rr03-84.djvu new file mode 100644 index 0000000000000000000000000000000000000000..39340109be83d7660baaad2137ae0567a1b1c98e GIT binary patch literal 69599 zcmaHSLy#^^uQ`rm2<0BFJi09HN#K-L}ruq6WkB3uE0 z%4`5&NErY)s0083&VGMh`XUKr>B^NYjIz-6XT@$|C57Yn)4#2*p3Teof_RXo*mp;~ z`yetyPp+6#DKUTr=zrR!aka8^l_6{UKlLzy6nl%TAdBqak2`dD`gP7z7|X}lpy6?u z|A!#}XYD_RDw48da{p0-hN^>W#sts+p#v#d8hQc%I351*a`!r(-~RIrb&LUDb*%=9 z$R-R~s!M)D(RC8j%Ox$qPzD9_%iO zmJ-8`DJNTV{1XDyejGm$|61;z=li+y{t10t=$6}~IkqYsH)dmtf!0iEj42#ua7icm zIb)7dY`J_7IH4L1_F9=IDJ_KjK0&PTev0rgn=YX6(RTo{PCw-D^QN*(*=Km$65cT8 z4^}>lW zXF7n=T(JQG#7;VfL2Ip)LG~*NauLe?L@3nouFU1Py3i($v`@lx<0+2nO^d=Skl!EQ zaM1UF@y&rSS7lH!cXgo z*{B8~UImXbUoz!1tWg`&s`bOW*o*^9oG+0qT&$|1L%_Wu%DYk8d7ZGmUBIqyOm6Rg zACQ=CUHaBSulVQ74CFx5jEx2yW)mQ&O3cY+1J@lC4eHKgtP^BjSy70#Kpj6DxU@-9 zU8Le6|Lq&vlLV=^3_2H~|13VspQ84g2ciKAl@ 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samy.bib


+@TECHREPORT{bengio:2003:idiap:03-83,
+  AUTHOR = {S. Bengio and J. Mari\'ethoz},
+  TITLE = {A Statistical Significance Test for Person Authentication},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-83},
+  URL = {publications/orig/rr03-83.ps.gz},
+  PDF = {publications/pdf/rr03-83.pdf},
+  DJVU = {publications/djvu/rr03-83.djvu},
+  ORIGINAL = {orig/rr03-83.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{bengio:2003:idiap:03-84,
+  AUTHOR = {S. Bengio and J. Mari\'ethoz},
+  TITLE = {The Expected Performance Curve for Person Authentication},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-84},
+  URL = {publications/orig/rr03-84.ps.gz},
+  PDF = {publications/pdf/rr03-84.pdf},
+  DJVU = {publications/djvu/rr03-84.djvu},
+  ORIGINAL = {orig/rr03-84.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{bengio:2003:idiap:03-85,
+  AUTHOR = {S. Bengio and M. Keller and J. Mari\'ethoz},
+  TITLE = {The Expected Performance Curve},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-85},
+  URL = {publications/orig/rr03-85.ps.gz},
+  PDF = {publications/pdf/rr03-85.pdf},
+  DJVU = {publications/djvu/rr03-85.djvu},
+  ORIGINAL = {orig/rr03-85.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{cardinaux:2003:idiap:03-76,
+  AUTHOR = {F. Cardinaux and C. Sanderson and S. Bengio},
+  TITLE = {Adapted Generative Models for Face Verification},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-76},
+  URL = {publications/orig/rr03-75.ps.gz},
+  PDF = {publications/pdf/rr03-76.pdf},
+  DJVU = {publications/djvu/rr03-76.djvu},
+  ORIGINAL = {orig/rr03-76.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{chiappa:2003:idiap-03-49,
+  AUTHOR = {S. Chiappa and S. Bengio},
+  TITLE = {{HMM} and {IOHMM} Modeling of {EEG} Rhythms for Asynchronous {BCI} Systems},
+  INSTITUTION = {IDIAP},
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-49},
+  YEAR = 2003,
+  URL = {publications/orig/rr03-49.ps.gz},
+  PDF = {publications/pdf/rr03-49.pdf},
+  DJVU = {publications/djvu/rr03-49.djvu},
+  ORIGINAL = {orig/rr03-49.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{collobert:2003:idiap-03-16,
+  AUTHOR = {R. Collobert and S. Bengio},
+  TITLE = {A New Margin-Based Criterion for Efficient Gradient Descent},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-16},
+  URL = {publications/orig/rr03-16.ps.gz},
+  PDF = {publications/pdf/rr03-16.pdf},
+  DJVU = {publications/djvu/rr03-16.djvu},
+  ORIGINAL = {orig/rr03-16.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{dimitrakakis:2003:idiap:03-69,
+  AUTHOR = {C. Dimitrakakis and S. Bengio},
+  TITLE = {Online Policy Adaptation for Ensemble Classifiers},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-69},
+  URL = {publications/orig/rr03-69.ps.gz},
+  PDF = {publications/pdf/rr03-69.pdf},
+  DJVU = {publications/djvu/rr03-69.djvu},
+  ORIGINAL = {orig/rr03-69.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{dimitrakakis:2003:idiap:03-41,
+  AUTHOR = {C. Dimitrakakis and S. Bengio},
+  TITLE = {Boosting {HMMs} with an application to speech recognition},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-41},
+  URL = {publications/orig/rr03-41.ps.gz},
+  PDF = {publications/pdf/rr03-41.pdf},
+  DJVU = {publications/djvu/rr03-41.djvu},
+  ORIGINAL = {orig/rr03-41.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{doss:2003:idiap:03-52,
+  AUTHOR = {M. Magimai.-Doss and S. Bengio and H. Bourlard},
+  TITLE = {Joint Decoding for Phoneme-Grapheme Continuous Speech Recognition},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-52},
+  URL = {publications/orig/rr03-52.ps.gz},
+  PDF = {publications/pdf/rr03-52.pdf},
+  DJVU = {publications/djvu/rr03-52.djvu},
+  ORIGINAL = {orig/rr03-52.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{keller:2003:idiap-03-74,
+  AUTHOR = {M. Keller and S. Bengio},
+  TITLE = {Textual Data Representation},
+  INSTITUTION = {IDIAP},
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-49},
+  YEAR = 2003,
+  URL = {publications/orig/rr03-74.ps.gz},
+  PDF = {publications/pdf/rr03-74.pdf},
+  DJVU = {publications/djvu/rr03-74.djvu},
+  ORIGINAL = {orig/rr03-74.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{mariethoz:2003:idiap-03-51,
+  AUTHOR = {J. Mari\'ethoz and S. Bengio},
+  TITLE = {An Alternative To Silence Removal For Text-Independent Speaker Verification},
+  INSTITUTION = {IDIAP},
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-51},
+  YEAR = 2003,
+  URL = {publications/orig/rr03-51.ps.gz},
+  PDF = {publications/pdf/rr03-51.pdf},
+  DJVU = {publications/djvu/rr03-51.djvu},
+  ORIGINAL = {orig/rr03-51.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{mccowan:2003:idiap-03-27,
+  AUTHOR = {I. McCowan and D. Gatica-Perez and S. Bengio and G. Lathoud},
+  TITLE = {Automatic Analysis of Multimodal Group Actions in Meetings},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-27},
+  URL = {publications/orig/rr03-27.ps.gz},
+  PDF = {publications/pdf/rr03-27.pdf},
+  DJVU = {publications/djvu/rr03-27.djvu},
+  ORIGINAL = {orig/rr03-27.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{mccowan:2003:idiap-com-03-10,
+  AUTHOR = {I. McCowan and D. Gatica-Perez and S. Bengio},
+  TITLE = {Meeting Data Collection Specifications},
+  INSTITUTION = {IDIAP},
+  YEAR = {2003},
+  TYPE = {Communication Report IDIAP-COM},
+  NUMBER = {03-10},
+  URL = {publications/orig/com03-10.ps.gz},
+  PDF = {publications/pdf/com03-10.pdf},
+  DJVU = {publications/djvu/com03-10.djvu},
+  ORIGINAL = {orig/com03-10.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{poh:2003:idiap-03-17,
+  AUTHOR = {N. Poh and S. Bengio},
+  TITLE = {Variance Reduction Techniques in Biometric Authentication},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-17},
+  URL = {publications/orig/rr03-17.ps.gz},
+  PDF = {publications/pdf/rr03-17.pdf},
+  DJVU = {publications/pdf/rr03-17.djvu},
+  ORIGINAL = {orig/rr03-17.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{poh:2003:idiap:03-59,
+  AUTHOR = {N. Poh and S. Bengio},
+  TITLE = {Why Do Multi-Stream, Multi-Band and Multi-Modal Approaches Work
+    on Biometric User Authentication Tasks?},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  NUMBER = {03-59},
+  TYPE = {Technical Report IDIAP-RR},
+  URL = {publications/orig/rr03-59.ps.gz},
+  PDF = {publications/pdf/rr03-59.pdf},
+  DJVU = {publications/djvu/rr03-59.djvu},
+  ORIGINAL = {orig/rr03-59.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{poh:2003:idiap-03-62,
+  AUTHOR = {N. Poh and C. Sanderson and S. Bengio},
+  TITLE = {An Investigation of Spectral Subband Centroids for Speaker Authentication},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  NUMBER = {03-62},
+  TYPE = {Technical Report IDIAP-RR},
+  URL = {publications/orig/rr03-62.ps.gz},
+  PDF = {publications/pdf/rr03-62.pdf},
+  DJVU = {publications/djvu/rr03-62.djvu},
+  ORIGINAL = {orig/rr03-62.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{pozdnoukhov:2003:idiap-03-29,
+  AUTHOR = {A. Pozdnoukhov and S. Bengio},
+  TITLE = {From Samples to Objects in Kernel Methods},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-29},
+  URL = {publications/orig/rr03-29.ps.gz},
+  PDF = {publications/pdf/rr03-29.pdf},
+  DJVU = {publications/djvu/rr03-29.djvu},
+  ORIGINAL = {orig/rr03-29.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{pozdnoukhov:2003:idiap:03-75,
+  AUTHOR = {A. Pozdnoukhov and S. Bengio},
+  TITLE = {Tangent Vector Kernels for Invariant Image Classification with {SVMs}},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  NUMBER = {03-75},
+  TYPE = {Technical Report IDIAP-RR},
+  URL = {publications/orig/rr03-75.ps.gz},
+  PDF = {publications/pdf/rr03-75.pdf},
+  DJVU = {publications/djvu/rr03-75.djvu},
+  ORIGINAL = {orig/rr03-75.ps.gz},
+  CATEGORIE = {E}
+}
+
+
+@TECHREPORT{wet:2003:idiap-03-08,
+  AUTHOR = {F. de Wet and K. Weber and L. Boves and B. Cranen and S. Bengio and H. Bourlard},
+  TITLE = {Evaluation of Formant-Like Features for Automatic Speech Recognition},
+  INSTITUTION = {IDIAP},
+  YEAR = 2003,
+  TYPE = {Technical Report IDIAP-RR},
+  NUMBER = {03-08},
+  URL = {publications/orig/rr03-08.ps.gz},
+  PDF = {publications/pdf/rr03-08.pdf},
+  DJVU = {publications/djvu/rr03-08.djvu},
+  ORIGINAL = {orig/rr03-08.ps.gz},
+  CATEGORIE = {E}
+}
+
+
\ No newline at end of file diff --git a/torch3/forum.html b/torch3/forum.html new file mode 100644 index 0000000..10269c8 --- /dev/null +++ b/torch3/forum.html @@ -0,0 +1,55 @@ + + + + + + Torch3' Documentation + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +

Forum

+ +
+ + + + +
+
+
+In this great world, some people believe it is a great thing to spam +forums like we had for Torch.

+ +These annoying guys must be thus very proud:

+ +The forum will remain closed until the next version of Torch. +

+ +PS: We do not need VIAGRA, or some other enlarging tools.

+
+
+ +

+
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b/torch3/index.html new file mode 100644 index 0000000..e5c47ec --- /dev/null +++ b/torch3/index.html @@ -0,0 +1,191 @@ + + + + + + Torch3: The Dream Comes True + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+

+ +

What's Torch ?

+ +
+ It's a machine-learning library, written in simple + C++ and distributed now under a BSD license.
+ Torch is currently developed at Idiap Research Institute, in Switzerland mountains.
+
+Update: You might want to have a look at Torch5. We will update this website soon... +
+
+
+
+ + + + + + + + + + + + + + + + +
The Torch Team
RonanSamyJohnny
Ronan Collobert
(The Guru)
Samy Bengio
(Distributions Wizard)
Johnny Mariéthoz
(Capt'ain Debug)
+
+ +
+
+
+ + + + +
+
+ +Release 3.1 +
+August 11, 2004 +
+
+ +
+
+ + + + +
+
+ +Torch 3 Vision +

+A full additional package for machine learning applied to vision applications is now available.
+Have a look here.


+
+
+ +
+ +
+
+

Aknowledgements

+
+If you are using Torch for your scientific research, please refer to the following paper: +
+R. Collobert, S. Bengio, and J. Mariéthoz. Torch: a modular machine learning software library. Technical Report IDIAP-RR 02-46, IDIAP, 2002. +
+
+ +
+

Features

+ +
+
    +
  • A lot of things in gradient machines, that is, machines which could + be learned with a gradient descent. This includes multi-layered perceptrons, + radial basis functions, mixtures of experts, convolutional networks + and even time-delay neural networks. In fact a lot of "modules" are available + that you can plug as you want to get what you need. +
  • + +
  • Support vector machines, in classification and regression. + As fast as the old stand-alone program SVMTorch II, but with the powerful + environment of the library. +
  • + +
  • Ensemble models such as bagging or adaboost. +
  • + +
  • Non-parametric models such as K-nearest-neighbors, Parzen + regression and Parzen density estimator. +
  • + +
  • Distributions stuff, like Kmeans, Gaussian mixture models, + hidden Markov models, input-output hidden Markov models, + and Bayes classifier.
  • + +
  • Speech recognition tools (Embedded training and large vocabulary decoding).
  • + +
+
+ +
+

Platforms

+ +
+ Torch3 has been successfully tested on Linux, + SunOS, FreeBSD, OSF1, Mac OS X and even MS Windows.
+
+ +
+

Motivation

+ +
+ Seven reasons to use Torch3:
+ +
    +
  • It's free
  • +
  • It's modular
  • +
  • It's growing
  • +
  • It has been though to be efficient
  • +
  • It has been designed to be intuitive
  • +
  • It contains a lot of state-of-the-art algorithms
  • +
  • Even if you don't like coding, it contains nice examples
  • +
+ You cannot imagine what we are doing for you!
+
+ +
+

Please...

+
+
    +
  • + Torch3 is free, distributed under a BSD license. That's pretty cool for you, + but we need your feedback. Cite Torch in your papers! Advertise it! + Send us a mail, an e-mail, something which says that you're using the library, and may encourage us. A nice postcard, + a picture from your country (or of your girlfriends!), or even money. We are reachable at the following address: +
    + Ronan Collobert and Samy Bengio and Johnny Mariéthoz
    + Idiap Research Institute
    + Centre du Parc
    + Rue Marconi 19
    + CP 592
    + 1920 Martigny
    + Switzerland
    +
    +
  • +
  • + If you have implemented a new machine algorithm or something wich could be cool to be added to the library, send us your code! +We need your contribution! +
  • +
+
+
+ + diff --git a/torch3/introduction.html b/torch3/introduction.html new file mode 100644 index 0000000..e5c47ec --- /dev/null +++ b/torch3/introduction.html @@ -0,0 +1,191 @@ + + + + + + Torch3: The Dream Comes True + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +

What's Torch ?

+ +
+ It's a machine-learning library, written in simple + C++ and distributed now under a BSD license.
+ Torch is currently developed at Idiap Research Institute, in Switzerland mountains.
+
+Update: You might want to have a look at Torch5. We will update this website soon... +
+
+
+
+ + + + + + + + + + + + + + + + +
The Torch Team
RonanSamyJohnny
Ronan Collobert
(The Guru)
Samy Bengio
(Distributions Wizard)
Johnny Mariéthoz
(Capt'ain Debug)
+
+ +
+
+
+ + + + +
+
+ +Release 3.1 +
+August 11, 2004 +
+
+ +
+
+ + + + +
+
+ +Torch 3 Vision +

+A full additional package for machine learning applied to vision applications is now available.
+Have a look here.


+
+
+ +
+ +
+
+

Aknowledgements

+
+If you are using Torch for your scientific research, please refer to the following paper: +
+R. Collobert, S. Bengio, and J. Mariéthoz. Torch: a modular machine learning software library. Technical Report IDIAP-RR 02-46, IDIAP, 2002. +
+
+ +
+

Features

+ +
+
    +
  • A lot of things in gradient machines, that is, machines which could + be learned with a gradient descent. This includes multi-layered perceptrons, + radial basis functions, mixtures of experts, convolutional networks + and even time-delay neural networks. In fact a lot of "modules" are available + that you can plug as you want to get what you need. +
  • + +
  • Support vector machines, in classification and regression. + As fast as the old stand-alone program SVMTorch II, but with the powerful + environment of the library. +
  • + +
  • Ensemble models such as bagging or adaboost. +
  • + +
  • Non-parametric models such as K-nearest-neighbors, Parzen + regression and Parzen density estimator. +
  • + +
  • Distributions stuff, like Kmeans, Gaussian mixture models, + hidden Markov models, input-output hidden Markov models, + and Bayes classifier.
  • + +
  • Speech recognition tools (Embedded training and large vocabulary decoding).
  • + +
+
+ +
+

Platforms

+ +
+ Torch3 has been successfully tested on Linux, + SunOS, FreeBSD, OSF1, Mac OS X and even MS Windows.
+
+ +
+

Motivation

+ +
+ Seven reasons to use Torch3:
+ +
    +
  • It's free
  • +
  • It's modular
  • +
  • It's growing
  • +
  • It has been though to be efficient
  • +
  • It has been designed to be intuitive
  • +
  • It contains a lot of state-of-the-art algorithms
  • +
  • Even if you don't like coding, it contains nice examples
  • +
+ You cannot imagine what we are doing for you!
+
+ +
+

Please...

+
+
    +
  • + Torch3 is free, distributed under a BSD license. That's pretty cool for you, + but we need your feedback. Cite Torch in your papers! Advertise it! + Send us a mail, an e-mail, something which says that you're using the library, and may encourage us. A nice postcard, + a picture from your country (or of your girlfriends!), or even money. We are reachable at the following address: +
    + Ronan Collobert and Samy Bengio and Johnny Mariéthoz
    + Idiap Research Institute
    + Centre du Parc
    + Rue Marconi 19
    + CP 592
    + 1920 Martigny
    + Switzerland
    +
    +
  • +
  • + If you have implemented a new machine algorithm or something wich could be cool to be added to the library, send us your code! +We need your contribution! +
  • +
+
+
+ + diff --git a/torch3/license.html b/torch3/license.html new file mode 100644 index 0000000..4b3d164 --- /dev/null +++ b/torch3/license.html @@ -0,0 +1,77 @@ + + + + + + Torch3' Documentation + + + + + + + + + + + + + + +
Torch3
  Introduction  

  Documentation  

  Downloads  

  Forum  

  Credits  
+ + +

License

+ +
+ + + + +
+
+Copyright (c) 2003 Ronan Collobert (IDIAP, Trebolloc & Co)
+Copyright (c) 2003 Samy Bengio (IDIAP)
+Copyright (c) 2003 Johnny Mariéthoz (IDIAP)
+
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met:
+
    +
  • Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. +
  • +
  • Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. +
  • +
  • The name of the author may not be used to endorse or promote products + derived from this software without specific prior written permission. +
  • +
+
+THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR +IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES +OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. +IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, +INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT +NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF +THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +
+
+ +

+
+ + diff --git a/torch3/license.txt b/torch3/license.txt new file mode 100644 index 0000000..cac8ff4 --- /dev/null +++ b/torch3/license.txt @@ -0,0 +1,27 @@ +Copyright (c) 2003 Ronan Collobert (IDIAP, Trebolloc & Co) +Copyright (c) 2003 Samy Bengio (IDIAP) +Copyright (c) 2003 Johnny Mariéthoz (IDIAP) + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. +2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. +3. The name of the author may not be used to endorse or promote products + derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR +IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES +OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. +IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, +INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT +NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF +THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/torch3/manual/Allocator.html b/torch3/manual/Allocator.html new file mode 100644 index 0000000..0b9ea87 --- /dev/null +++ b/torch3/manual/Allocator.html @@ -0,0 +1,155 @@ + + + + + class Allocator + + + + +

class Allocator

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Class do easily allocate/deallocate memory in Torch.
+
+ +
+

+

Public Methods

+[more] Allocator() +
Create a new allocator +
+[more]void* alloc(size_t size, int object_style=0) +
Returns size bytes of allocated memory. +
+[more]void* realloc(void* ptr, size_t size) +
Reallocate a part of the memory which has been already allocated with alloc (and object_style=0). +
+[more]void free(void* ptr) +
Force given pointer to memory to be freed now. +
+[more]void retain(void* ptr, int object_style=0) +
Tells to the allocator that it should handle the memory given by ptr. +
+[more]int release(void* ptr) +
Tells to the allocator to stop taking in account the memory given by ptr. +
+[more]void steal(void* ptr, Allocator* allocator) +
Handles the memory given by ptr which was previouly handled by allocator. +
+[more]void steal(Allocator* allocator) +
Steals all pointers contained in allocator +
+[more]AllocatorNode* isMine(void* ptr) +
Returns true iff ptr is handled by the allocator +
+[more]void freeAll() +
Force all pointers contained in the allocator to be freed now. +
+[more]static void* sysAlloc(int size) +
System allocation. +
+[more]static void* sysRealloc(void* ptr, int size) +
System reallocation. +

+ +
+ + +
+

Documentation

+
Class do easily allocate/deallocate memory in Torch. +The memory allocated by an allocator will be destroyed +when the allocator will be destroyed. + +

+
+ + + +
o Allocator() +
Create a new allocator +

+ + +

ovoid* alloc(size_t size, int object_style=0) +
Returns size bytes of allocated memory. +
    +
  • If object_style is 0, the allocated memory is +considered as if it wasn't for an object. At the destruction +of the allocator the memory will be freed, and that's all. +
  • If 1, the Object destructor will be called +at the destruction and the memory will be freed. +
  • If 2, the destructor will be called, but the memory +won't be freed. +
+

+ + +

ovoid* realloc(void* ptr, size_t size) +
Reallocate a part of the memory which has been already +allocated with alloc (and object_style=0). +Same behaviour as the realloc() system function. +

+ + +

ovoid free(void* ptr) +
Force given pointer to memory to be freed now. +It considers the object_style given by alloc() +and calls the Object destructor, if needed. +

+ + +

ovoid retain(void* ptr, int object_style=0) +
Tells to the allocator that it should handle the memory +given by ptr. Take in account the object_style. +

+ + +

oint release(void* ptr) +
Tells to the allocator to stop taking in account the +memory given by ptr. The memory will not be released. +

+ + +

ovoid steal(void* ptr, Allocator* allocator) +
Handles the memory given by ptr which was previouly +handled by allocator. allocator looses the control +of this memory +

+ + +

ovoid steal(Allocator* allocator) +
Steals all pointers contained in allocator +

+ + +

oAllocatorNode* isMine(void* ptr) +
Returns true iff ptr is handled by the allocator +

+ + +

ovoid freeAll() +
Force all pointers contained in the allocator to be freed now. +It considers the object_style given by alloc() +and calls the Object destructor, if needed. +

+ + +

ostatic void* sysAlloc(int size) +
System allocation. +As system malloc function, but do an error if there is no more memory. +

+ + +

ostatic void* sysRealloc(void* ptr, int size) +
System reallocation. +As system realloc function, but do an error if there is no more memory. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
Object +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Bagging.html b/torch3/manual/Bagging.html new file mode 100644 index 0000000..e8f10ee --- /dev/null +++ b/torch3/manual/Bagging.html @@ -0,0 +1,174 @@ + + + + + class Bagging + + + + +

class Bagging

This class represents a Trainer that implements the well-known Bagging algorithm (Breiman, 1996).
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]WeightedSumMachine* w_machine +
This machine performs the combination. +
+[more]int n_trainers +
The number of trainers in the bagging +
+[more]int** unselected_examples +
for each trainer, keep the indices of examples not used during training +
+[more]int** selected_examples +
for each trainer, keep the indices of examples used during training +
+[more]int* n_unselected_examples +
for each trainer, keep the number of examples not used during training +
+[more]int* is_selected_examples +
for each trainer, keep the number of examples used during training +

+ +

+

Public Methods

+[more] Bagging(WeightedSumMachine* w_machine) +
+[more]virtual void bootstrapData(int* selected, int* is_selected, int n_examples) +
create a boostrap of the data and put in in selected +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class represents a Trainer that implements the well-known +Bagging algorithm (Breiman, 1996). A "bagger" contains a series +of trainers, each trained on a bootstrap of the original dataset. +The output of the bagging is then the average of the output of +each trainer. + +

It is implemented using a WeightedSumMachine that performs the combination. + +

+
+ + + +
oWeightedSumMachine* w_machine +
This machine performs the combination. It contains many trainers. +

+ + +

oint n_trainers +
The number of trainers in the bagging +

+ + +

oint** unselected_examples +
for each trainer, keep the indices of examples not used during training +

+ + +

oint** selected_examples +
for each trainer, keep the indices of examples used during training +

+ + +

oint* n_unselected_examples +
for each trainer, keep the number of examples not used during training +

+ + +

oint* is_selected_examples +
for each trainer, keep the number of examples used during training +

+ + +

o Bagging(WeightedSumMachine* w_machine) +

+ + +

ovirtual void bootstrapData(int* selected, int* is_selected, int n_examples) +
create a boostrap of the data and put in in selected +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) + +
See Also:
WeightedSumMachine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/BayesClassifier.html b/torch3/manual/BayesClassifier.html new file mode 100644 index 0000000..2534362 --- /dev/null +++ b/torch3/manual/BayesClassifier.html @@ -0,0 +1,149 @@ + + + + + class BayesClassifier + + + + +

class BayesClassifier

A multi class bayes classifier -- maximizes the likelihood of each class separately using a trainer for distribution.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]BayesClassifierMachine* bayesmachine +
the bayes machine +
+[more]int n_classes +
the number of different classes +
+[more]int** classes +
all the example indices of each class +
+[more]int* classes_n +
the number of examples per class +

+ +

+

Public Methods

+[more] BayesClassifier( BayesClassifierMachine* ) +
you need to define a BayesClassifierMachine to use this class +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A multi class bayes classifier -- maximizes the likelihood of each class +separately using a trainer for distribution. When testing, the predicted +class corresponds to the trainer giving the maximum output, weighted by +its prior probability. + +

+
+ + + +
oBayesClassifierMachine* bayesmachine +
the bayes machine +

+ + +

oint n_classes +
the number of different classes +

+ + +

oint** classes +
all the example indices of each class +

+ + +

oint* classes_n +
the number of examples per class +

+ + +

o BayesClassifier( BayesClassifierMachine* ) +
you need to define a BayesClassifierMachine to use this class +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Bison Ravi (francois.belisle@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/BayesClassifierMachine.html b/torch3/manual/BayesClassifierMachine.html new file mode 100644 index 0000000..9163aa3 --- /dev/null +++ b/torch3/manual/BayesClassifierMachine.html @@ -0,0 +1,196 @@ + + + + + class BayesClassifierMachine + + + + +

class BayesClassifierMachine

BayesClassifierMachine is the machine used by the BayesClassifier trainer to perform a Bayes Classification using different distributions.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_trainers +
the number of classes corresponds to the number of Trainer +
+[more]int n_outputs +
the number of outputs in this machine +
+[more]EMTrainer** trainers +
the actual trainers (EMTrainer since we are training distributions) +
+[more]real* log_priors +
the log_prior probabilities of each class. +
+[more]Sequence* log_probabilities +
it contains the log posterior probability plus the log prior of the class +
+[more]bool allocated_log_priors +
used to know if log_priors where given or allocated +
+[more]ClassFormat* class_format +
the class format of the output +
+[more]MeasurerList** trainers_measurers +
the measurers for each individual trainer +

+ +

+

Public Methods

+[more] BayesClassifierMachine( EMTrainer**, int n_trainers_, MeasurerList** trainers_measurers_, ClassFormat* class_format_, real* log_priors_=NULL) +
creates a machine for BayesClassifier trainers, given a vector of trainers (one per class), an associate measurer for each trainer, a class_format that explains how the classes are coded, and an eventual vector (of size n_trainers_) containing the log of the class priors +
+[more]virtual void forward(Sequence* inputs) +
definition of virtual functions of Machine +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
BayesClassifierMachine is the machine used by the BayesClassifier +trainer to perform a Bayes Classification using different distributions. +The output corresponds to the class that is the most probable +(using prior AND posterior information). + +

+
+ + + +
oint n_trainers +
the number of classes corresponds to the number of Trainer +

+ + +

oint n_outputs +
the number of outputs in this machine +

+ + +

oEMTrainer** trainers +
the actual trainers (EMTrainer since we are training distributions) +

+ + +

oreal* log_priors +
the log_prior probabilities of each class. default: log_priors are +taken as the log of the proportions in the training set. +

+ + +

oSequence* log_probabilities +
it contains the log posterior probability plus the log prior of the class +

+ + +

obool allocated_log_priors +
used to know if log_priors where given or allocated +

+ + +

oClassFormat* class_format +
the class format of the output +

+ + +

oMeasurerList** trainers_measurers +
the measurers for each individual trainer +

+ + +

o BayesClassifierMachine( EMTrainer**, int n_trainers_, MeasurerList** trainers_measurers_, ClassFormat* class_format_, real* log_priors_=NULL) +
creates a machine for BayesClassifier trainers, given a vector of +trainers (one per class), an associate measurer for each trainer, +a class_format that explains how the classes are coded, and an eventual +vector (of size n_trainers_) containing the log of the class priors +

+ + +

ovirtual void forward(Sequence* inputs) +
definition of virtual functions of Machine +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Bison Ravi (francois.belisle@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/BeamSearchDecoder.html b/torch3/manual/BeamSearchDecoder.html new file mode 100644 index 0000000..4228b37 --- /dev/null +++ b/torch3/manual/BeamSearchDecoder.html @@ -0,0 +1,83 @@ + + + + + class BeamSearchDecoder + + + + +

class BeamSearchDecoder

This class implements a Viterbi decoder with beam search capabilities.
+
+ +
+

+

Public Members

+[more] Decodes using the input data vectors in 'input_data' +
+[more] 'n_frames_' is the number of vectors of input data +
+[more] 'vec_size' is the number of elements in each vector. +
+[more] features or emission probabilities and 'vec_size' must reflect this +
+[more] After this function returns, 'num_result_words' contains the number of words +
+[more] recognised and 'result_words' contains the vocabulary indices of the recognised +

+ +
+ + +
+

Documentation

+
This class implements a Viterbi decoder with beam search +capabilities. A Lexicon and LanguageModel are required at +creation time (the LanguageModel is optional). By default, +no pruning occurs. Two levels of pruning can be configured - +word interior hypothesis pruning and word end hypothesis pruning. +The application of language model probabilities can be +delayed or performed normally. + +

+
+ + + +
o Decodes using the input data vectors in 'input_data' +
Decodes using the input data vectors in 'input_data' +

+ + +

o 'n_frames_' is the number of vectors of input data +
'n_frames_' is the number of vectors of input data +

+ + +

o 'vec_size' is the number of elements in each vector. +
'vec_size' is the number of elements in each vector. The input data can be either +

+ + +

o features or emission probabilities and 'vec_size' must reflect this +
features or emission probabilities and 'vec_size' must reflect this +

+ + +

o After this function returns, 'num_result_words' contains the number of words +
After this function returns, 'num_result_words' contains the number of words +

+ + +

o recognised and 'result_words' contains the vocabulary indices of the recognised +
recognised and 'result_words' contains the vocabulary indices of the recognised +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/BoolCmdOption.html b/torch3/manual/BoolCmdOption.html new file mode 100644 index 0000000..bfdc605 --- /dev/null +++ b/torch3/manual/BoolCmdOption.html @@ -0,0 +1,128 @@ + + + + + class BoolCmdOption + + + + +

class BoolCmdOption

This class defines a bool command-line option.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] BoolCmdOption(const char* name_, bool* ptr_, bool init_value_, const char* help_="", bool save_=false) +

+ +
+

Inherited from CmdOption:

+
+

+

Public Fields

+ochar* name +
+ochar* type_name +
+ochar* help +
+obool save +
+obool is_setted +

+ +

+

Public Methods

+ovirtual void initValue() +
+ovirtual void printValue(XFile* file_) +
+ovirtual void read(int* argc_, char*** argv_) +
+obool isOption(bool set_=false) +
+obool isArgument(bool set_=false) +
+obool isText(bool set_=false) +
+obool isMasterSwitch(bool set_=false) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class defines a bool command-line option. + +

+
+ + + +
o BoolCmdOption(const char* name_, bool* ptr_, bool init_value_, const char* help_="", bool save_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Boosting.html b/torch3/manual/Boosting.html new file mode 100644 index 0000000..ae72f9c --- /dev/null +++ b/torch3/manual/Boosting.html @@ -0,0 +1,151 @@ + + + + + class Boosting + + + + +

class Boosting

Boosting implementation.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]WeightedSumMachine* w_machine +
This machine performs the combination. +
+[more]ClassFormat* class_format +
ClassFormat to know how the classes are encoded +
+[more]int n_trainers +
The number of trainers in the boosting +
+[more]real* weights +
The weights of each machine in the boosting +

+ +

+

Public Methods

+[more] Boosting(WeightedSumMachine* w_machine_, ClassFormat* class_format_) +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Boosting implementation. +As the idea of boosting in regression hasn't been really well tested, +this is boosting for *classification* only. + +

This trainer will "boost" the machine given by the WeightedSumMachine, +on the given DataSet. + +

You have to provide a ClassFormat to know how the classes are encoded. + +

+
+ + + +
oWeightedSumMachine* w_machine +
This machine performs the combination. It contains many trainers. +

+ + +

oClassFormat* class_format +
ClassFormat to know how the classes are encoded +

+ + +

oint n_trainers +
The number of trainers in the boosting +

+ + +

oreal* weights +
The weights of each machine in the boosting +

+ + +

o Boosting(WeightedSumMachine* w_machine_, ClassFormat* class_format_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
WeightedSumMachine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/BoostingMeasurer.html b/torch3/manual/BoostingMeasurer.html new file mode 100644 index 0000000..e79b955 --- /dev/null +++ b/torch3/manual/BoostingMeasurer.html @@ -0,0 +1,151 @@ + + + + + class BoostingMeasurer + + + + +

class BoostingMeasurer

Compute the classification weighted error (in %) for BoostingMachine of the inputs with respect to the targets of data.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] BoostingMeasurer(ClassFormat* class_format_, XFile* file_) +
+[more]virtual void setDataSet(DataSet* data_) +
Set the current working dataset +
+[more]virtual void setWeights(real* weights_) +
Set the current weights of training examples +
+[more]virtual void setInputs(Sequence* inputs_) +
Gives the pointer where the measure will be done +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Compute the classification weighted error (in %) for BoostingMachine +of the inputs with respect to the targets of data. +The weights are given by setWeights(). + +

Needed by Boosting. (Designed just for it). + +

The format of the class is given with a ClassFormat. + +

+
+ + + +
o BoostingMeasurer(ClassFormat* class_format_, XFile* file_) +

+ + +

ovirtual void setDataSet(DataSet* data_) +
Set the current working dataset +

+ + +

ovirtual void setWeights(real* weights_) +
Set the current weights of training examples +

+ + +

ovirtual void setInputs(Sequence* inputs_) +
Gives the pointer where the measure will be done +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +Samy Bengio (bengio@idiap.ch) + +
See Also:
Boosting

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ClassFormat.html b/torch3/manual/ClassFormat.html new file mode 100644 index 0000000..955ef83 --- /dev/null +++ b/torch3/manual/ClassFormat.html @@ -0,0 +1,151 @@ + + + + + class ClassFormat + + + + +

class ClassFormat

Used to define a class code.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_classes +
Number of classes that the object currently handles +
+[more]real** class_labels +
The label of each class +

+ +

+

Public Methods

+[more] ClassFormat() +
+[more]virtual int getOutputSize() = 0 +
Returns the output size +
+[more]virtual void fromOneHot(real* outputs, real* one_hot_outputs) = 0 +
Transforms the output from a OneHot representation +
+[more]virtual void toOneHot(real* outputs, real* one_hot_outputs) = 0 +
Transforms the output to a OneHot representation +
+[more]virtual int getClass(real* vector) = 0 +
Returns the class of vector +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Used to define a class code. + +

+
+ + + +
oint n_classes +
Number of classes that the object currently handles +

+ + +

oreal** class_labels +
The label of each class +

+ + +

o ClassFormat() +

+ + +

ovirtual int getOutputSize() = 0 +
Returns the output size +

+ + +

ovirtual void fromOneHot(real* outputs, real* one_hot_outputs) = 0 +
Transforms the output from a OneHot representation +

+ + +

ovirtual void toOneHot(real* outputs, real* one_hot_outputs) = 0 +
Transforms the output to a OneHot representation +

+ + +

ovirtual int getClass(real* vector) = 0 +
Returns the class of vector +

+
+
Direct child classes: +
TwoClassFormat
+OneHotClassFormat
+MultiClassFormat
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ClassFormatDataSet.html b/torch3/manual/ClassFormatDataSet.html new file mode 100644 index 0000000..c58bb15 --- /dev/null +++ b/torch3/manual/ClassFormatDataSet.html @@ -0,0 +1,178 @@ + + + + + class ClassFormatDataSet + + + + +

class ClassFormatDataSet

Given a DataSet, convert (on-the-fly) targets using a conversion table.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]DataSet* data +
The provided DataSet +
+[more]Sequence* class_labels +
The class label translation table +

+ +

+

Public Methods

+[more] ClassFormatDataSet(DataSet* data_, Sequence* class_labels_) +
Here you provide the translation table in class_labels_ +
+[more] ClassFormatDataSet(DataSet* data_, int n_classes=-1) +
We assume here that you want the one-hot encoding format. +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid init(int n_examples_, int n_inputs_, int n_targets_) +
+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Given a DataSet, convert (on-the-fly) targets using a conversion table. + +

The targets of the given DataSet should be 0,1,2... for the class 0, class 1, +class 2, and so on. Note that is must START AT 0. + +

After a setExample(), the inputs of this DataSet will be the same as +the provided one. The targets will be class_labels->frames[i], where i +is contained in the targets of the provided DataSet. + +

+
+ + + +
oDataSet* data +
The provided DataSet +

+ + +

oSequence* class_labels +
The class label translation table +

+ + +

o ClassFormatDataSet(DataSet* data_, Sequence* class_labels_) +
Here you provide the translation table in class_labels_ +

+ + +

o ClassFormatDataSet(DataSet* data_, int n_classes=-1) +
We assume here that you want the one-hot encoding format. +The number of classes is given by n_classes, if positive. +Otherwise, the number of classes is guessed by taking the +maximum value of the targets of the provided DataSet. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ClassGraph.class b/torch3/manual/ClassGraph.class new file mode 100644 index 0000000000000000000000000000000000000000..c6a7b6c79eefb07545a0b85e767db0a34067477d GIT binary patch literal 1237 zcma)6*-{fh6g@+hnS_afK|w^^#V{;!Ux zT+h!a)b2v}DxTm%X4(`QsclfhP)G8~Xw_zCWBVEWk6WrC% z+sJ92m^PjDN?b#NZYz*X$O3b#R&t&NRAdse&V07V8-1gWC{c{gs#ZqSPrp^7-UQnZ z?KrFRIdy|VGDj%h1IMLHu6NL0Y^2g$ccS9+UGDq5ly|-mxv0;BhLH$3@hyHT`(9Ph z8e-%(i$Uk6j})Y#zB-aUWUpeHWQM#$#1J9v+E%27i#gj0lUlW{9#U(z6(uzjwyhB9 zZ@6IpLUKD)hgHKU*~a$7aCmacu3?aVLv;-Nz_4w9$8Zhjw_3)f8b&DB+_tnj`fIrS bmF6i%^l#B((N9`2jM#PbwZroS^x)|~2>C-7 literal 0 HcmV?d00001 diff --git a/torch3/manual/ClassGraphPanel.class b/torch3/manual/ClassGraphPanel.class new file mode 100644 index 0000000000000000000000000000000000000000..94b21b47a2a4b19b981fbe8827197a5d71dffc7a GIT binary patch literal 4084 zcmbtWX>eOt75<*}q^IS@c9f{CsBM;#)Rq&Qlwuk?DI`uC3{KL!~;QmGKkLv@kkI~3F3P}{5*)?2JsgIA2je` z10ON)2?OU1e8a$F1}+$Q+`tnCo;2{3fo~f4mVs{@_>O_^8hAR44!k~$D@F9+4PkU* zJdAGa3u7bphtQ4#B5nyGid)0jfP*rf5OJGC91`ttnBqtnSK#(Ax-coWDG^7-<&7c4 z@Ftla3*$w2vuH_)utH2eEfJ|Ou0~qmZHbtX)mag90-BLpj?3x^an6dEm(`p= zv^zq$3I!2G6Zd0T#Ct@%PsIC8d=~F8@i{zf;`1WPc+kWbuxR3oIAh{VIA!9?a7;Xk z(I?{#OhTeL4qxo#UFe27OlXZR}pR;q$NW+(m z=Bq~ek~+lRg0(Q0Nfi~!Rjn4>w2cXBF=Jzw)-2Ur-GDQ0-I*^r`>dQbYrD0^yjAt3 z2d0mc%8@>jbZw*Eqp^{cv7BQIMr+U3l{hUhFZH~9i?y(jwVlCTY8cJ4qGe~q4bRbj z=-{{_a`*G5t$MjJE#ao7T*|NUK$=4u`$M?awrB|K$mBB4jhu{X2#;p1Vo~jphK~AV zK)Slga*LI-vl=4G$K59l`e;6FYgosRE3(C%!&bJ$xwePMH!Y{^1&7C>NCVG`HcrR! zhH&mpr}t$%J#Kqyh+fLChW7D%%E}(L3K?rUYZI_zzqOc|wVZrmcgb<`Il>=g&WU`f zkg{*iWTgmpN!w8-jvlRNalM&&gJ*1Hh%v`_2(5HlgWsBQ>;l=EwrBDM!uhAOR_cTp z@}*pwB^c8xGc`Sx$~mMa#TDna{0ZIygd&J9ogsvt&M&dRkPN#Dh5V9+V7g!}jc0Pi z4cK>-tSkfkGnqn>Fxnh>nzM@gn6?TQn6oppb6gB$a%mn`B4lc8chqj6Di`fFi(-`& zG#I?2-E7P`7OP>gb^Z7;YM<~Zrs(`p93uJ|4ht%lqmqze#L3X3Mmqpw0Xbw@W9gQLjVQ8^5T~xO` zyRo#uwka)mfqJPR`)(}Cp*b+an%NotrA%6C(paE&H^7(lO3DcT`6NeMwq8j-es*&%d8u^l`k&h@xga7yAy~O<}!JmQ2mmS*0#2Q|b=#1^rK8{VMvZdewk#v>ee53f^prM4$lu$liVZikpAINPKwVFp(% z*DFhimh-r|f>#~ThCAZz6>NV98!w=HG9HMxui={EjxzKkzM)RKE7QRp{_N0teJC0?qiq!oK8S#CC`yMuNqGUClks)&j<`S88H>i&)22!pSi{RE5|i}M zldG(rA9~&CXQK%QbWE<{#Z#*os^GQ0p-34wBm^xMVd9q`@zl;9L5f8NIBZr++x^+( zTrASrGgraL$%qz29MM9!OU8YB+zDwF+mKkU5n-*^r%jb9VkFd*N`& z?uPVtN%rP&{_1nXeGjnjLxAr-vb2r=eLm8=YXz@N>$0JK-%z0JOULzCAQsS*(tU?Qx*F@L(I3otzg;z8wi+Gp1NWR3pHH`(pY=$mj|l6tys zywNjy_)^TCa@$i(&ju%HQ+3#;-1JvlSgq~9%2{qZ#soYsOmL{bt6I%vCy-(#p_IV- zbu|-;DtL9dt&P|`nZ(|Inb=K>u+XoW14HSa-L+fR6(g17#U zngzLmo2{2{gTFElZv%2OcbRz_zp(+k+Dr|m7U`ClE}+uQ*ExA^8>@ZeZO~XfZEF6% zw67bu^JJhc7KpPEw(IFL|2pMf5gLAqcY0@h5dr=I$NSIW+6rFd8`8_Tl~oL_;0Ax% zcOJvM?{>y?N;xLda+_m1Px4M`eM;*c_Q(Az7!&cj2nih82>HF?q-+mL1DoFse%e^QYffI4N#SGSZ!&wS_MV3O}6RQWH)X$EyY{w zecz&Z;B=;=pVVmsBQuVl^)K+B5ufMXBu$0P>~p`*{l59@-{1d01bc8X23tizg`;9d z#j`42Qt`5iS5&;J;x!cuDqdIdhKe^;yrtr874PV1$L%^|xI;%L4lqbFxKo3MyL3cx zw+P>yBgt;Cs{VCqXT2?`5_JK@i2pN15-G~;0%MDfhsHplLltt8kj@Yz*#(EV4m4? zs2F$-rwu&M)C(+o5fcX9W9oedAK);2HQ7PaF6Qj~e)#V|>Yquh{rJ zgRdEUgU1bAVCq{uVcUs8^>}l1wf#tZif3PK7Ye8GCZ%l6b>Kc*8=;Vx@3mQ&ZGCNY8nj-K2 zGp|=$k9j?Fv(LYSt0rVo z@V&WVdx|v5wCxn8nQ+AJQVz{EZ#rEotnW{&u(>~!PxE+q8R+UXC1GhJmTMJkpE}f3 zh#Nw8NeI?YN)=zQ!T1>ttxt{>#7y{^Uz84Q>um=M+n3RBI#%%xs0vT zX*rTsmN1brl^V8Z)VNy1?o5o)&Wskx& zph%{YxOnyFB*nXdLhYb0l?`J?uON1+Zy7hymn6?w!h7l4LXNVRu<;j4mVfk@RWD(d z+N+XehO<8$8Cb%ZRDu%z6LKaRk8;j(Ji3fNIWAMS93~shGb&!j&DpfV%EWn?rb5CU zi`bSl6>9bpx`ZUP2u(;*3lS-?{o>WdMu$IYwy}!_#vN9;q+MZ-65eg(C?%-P>uEL{ zM9K9;snJW=oiZs!ku2rM$trP$`j()mf*4qcN@kS8{u4>dOZYowl9jM0L$;^6P+78Q z-;ZdIt0B39eQ`yo7XF)mWhr!`Z%040*vm{02*i<;0KkC}q*6CIis4)QD5 zzXUTLW1~J(3r9sl3P3a7Z-x;$gG62~W^1_RH{5y!ou^FsGWsuJQs_8(Zl|D6Z9j5;Sf~rkj literal 0 HcmV?d00001 diff --git a/torch3/manual/ClassMeasurer.html b/torch3/manual/ClassMeasurer.html new file mode 100644 index 0000000..4fc7890 --- /dev/null +++ b/torch3/manual/ClassMeasurer.html @@ -0,0 +1,123 @@ + + + + + class ClassMeasurer + + + + +

class ClassMeasurer

Compute the classification error (in %) of the inputs with respect to the targets of data.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] ClassMeasurer(Sequence* inputs_, DataSet* data_, ClassFormat* class_format_, XFile* file_, bool calc_confusion_at_each_iter_=false) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Compute the classification error (in %) +of the inputs with respect to the targets of data. + +

The format of the class is given with a ClassFormat. +It can print the confusion matrix if specified. + +

+
+ + + +
o ClassMeasurer(Sequence* inputs_, DataSet* data_, ClassFormat* class_format_, XFile* file_, bool calc_confusion_at_each_iter_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ClassNLLCriterion.html b/torch3/manual/ClassNLLCriterion.html new file mode 100644 index 0000000..b19e75d --- /dev/null +++ b/torch3/manual/ClassNLLCriterion.html @@ -0,0 +1,169 @@ + + + + + class ClassNLLCriterion + + + + +

class ClassNLLCriterion

This criterion can be used to train *in classification* a GradientMachine object using the StochasticGradient trainer.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] ClassNLLCriterion(ClassFormat* class_format) +
The ClassFormat is needed just to know how the targets are encoded in the dataset +

+ +
+

Inherited from Criterion:

+
+

+

Public Fields

+oDataSet* data +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* data_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This criterion can be used to train *in classification* a GradientMachine +object using the StochasticGradient trainer. It then maximizes the log +likelihood of the data. + +

If we write for the output of the GradientMachine, it supposes that +

    +
  • the outputs are log-probabilities. +
  • is the probability for the class +
  • the predicted class follows a multinomial distribution with parameters + +
+ +

The number of target frames in DataSet must +correspond to the number of input frames given +to this criterion. + +

+
+ + + +
o ClassNLLCriterion(ClassFormat* class_format) +
The ClassFormat is needed just to know how the targets are encoded in the dataset +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ClassNLLMeasurer.html b/torch3/manual/ClassNLLMeasurer.html new file mode 100644 index 0000000..b66481f --- /dev/null +++ b/torch3/manual/ClassNLLMeasurer.html @@ -0,0 +1,124 @@ + + + + + class ClassNLLMeasurer + + + + +

class ClassNLLMeasurer

This class measures the negative log likelihood.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] ClassNLLMeasurer(Sequence* inputs_, DataSet* data_, ClassFormat* class_format_, XFile* file_) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class measures the negative log likelihood. In fact, it supposes +that for each input frames, frames[i] is the log-probability for class . +The given class_format gives the class format of the targets of the dataset. + +

By default, the measurer divides the log-probabilty by the number of examples +and the number of frames. + +

+
+ + + +
o ClassNLLMeasurer(Sequence* inputs_, DataSet* data_, ClassFormat* class_format_, XFile* file_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/CmdLine.html b/torch3/manual/CmdLine.html new file mode 100644 index 0000000..468bd35 --- /dev/null +++ b/torch3/manual/CmdLine.html @@ -0,0 +1,287 @@ + + + + + class CmdLine + + + + +

class CmdLine

This class provides a useful interface for the user, to easily read some arguments/options from the command-line.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] CmdLine() +
+[more]int read(int argc_, char** argv_) +
Read the command-line. +
+[more]void help() +
Print the help. +
+[more]void addBCmdOption(const char* name, bool* ptr, bool init_value, const char* help="", bool save_it=false) +
+[more]void addRCmdOption(const char* name, real* ptr, real init_value, const char* help="", bool save_it=false) +
+[more]void addSCmdOption(const char* name, char** ptr, const char* init_value, const char* help="", bool save_it=false) +
+[more]void addBCmdArg(const char* name, bool* ptr, const char* help="", bool save_it=false) +
+[more]void addRCmdArg(const char* name, real* ptr, const char* help="", bool save_it=false) +
+[more]void addSCmdArg(const char* name, char** ptr, const char* help="", bool save_it=false) +
+[more]void addText(const char* text) +
Add a text line in the help message +
+[more]void info(const char* text) +
Add a text at the beginnig of the help +
+[more]void addMasterSwitch(const char* text) +
Add a master switch. +
+[more]void setWorkingDirectory(const char* dirname) +
Set the working directory. +
+[more]char* getPath(const char* filename) +
Get a full path. +
+[more]DiskXFile* getXFile(const char* filename) +
Get a DiskXFile. +
+[more]virtual void loadXFile(XFile* file) +
Load the object from a file pointer (not the options) +
+[more]virtual void saveXFile(XFile* file) +
Save the object to a file pointer (not the options) +
+[more]void addCmdOption(CmdOption* option) +
Add an option to the command line. +
+[more]void writeLog(XFile* file, bool write_associated_files) +
Write a log in file. +

+ +

+

Public Members

+[more] Functions for adding options. +
+[more] Functions for adding an argument. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class provides a useful interface for the user, +to easily read some arguments/options from the command-line. + +

Note that here, we make a difference between: +

    +
  • options which are not required. +
  • arguments which are required. +
+ +

Options: + +
+"write log" bool Should I output the cmd.log file ? [true] +
+ +

+
+ + + +
o CmdLine() +

+ + +

oint read(int argc_, char** argv_) +
Read the command-line. +Call this function after adding options/arguments +that you need, with the help of the following functions. +

+ + +

ovoid help() +
Print the help. +Call this function after adding options/arguments +that you need, with the help of the following functions. +

+ + +

o Functions for adding options. +
Functions for adding options. +The calling order of the following functions will +define the text order associated when you will call help(). + +

Add an option (Int, Bool, Real, String). +

    +
  • name the name of the option (must be unique). +
  • ptr is the pointer on the optional variable. +
  • init_value is the initialization value. +
  • help is the help text for this option. +
+ +

The option will be setted to value in the command-line +by printing "name value" +

+ + +

ovoid addBCmdOption(const char* name, bool* ptr, bool init_value, const char* help="", bool save_it=false) +

+ + +

ovoid addRCmdOption(const char* name, real* ptr, real init_value, const char* help="", bool save_it=false) +

+ + +

ovoid addSCmdOption(const char* name, char** ptr, const char* init_value, const char* help="", bool save_it=false) +

+ + +

o Functions for adding an argument. +
Functions for adding an argument. +The argument will be setted to value in the command-line +by writting "value" after all the options. +If there are N arguments, you have to write +"value1 value2 value3 ... valueN" to set them in the +command-line. +

+ + +

ovoid addBCmdArg(const char* name, bool* ptr, const char* help="", bool save_it=false) +

+ + +

ovoid addRCmdArg(const char* name, real* ptr, const char* help="", bool save_it=false) +

+ + +

ovoid addSCmdArg(const char* name, char** ptr, const char* help="", bool save_it=false) +

+ + +

ovoid addText(const char* text) +
Add a text line in the help message +

+ + +

ovoid info(const char* text) +
Add a text at the beginnig of the help +

+ + +

ovoid addMasterSwitch(const char* text) +
Add a master switch. +It creates an another type of command line. +If the text is the first argument of the user command line, +only the options corresponding to this new command line will be considered. +

+ + +

ovoid setWorkingDirectory(const char* dirname) +
Set the working directory. +Use it with getPath() and getXFile(). +

+ + +

ochar* getPath(const char* filename) +
Get a full path. +It adds the working_directory before the filename. +This path will be deleted by CmdLine. +

+ + +

oDiskXFile* getXFile(const char* filename) +
Get a DiskXFile. +It adds the working_directory before the filename and opens the file. +This XFile will be deleted by CmdLine. +

+ + +

ovirtual void loadXFile(XFile* file) +
Load the object from a file pointer (not the options) +

+ + +

ovirtual void saveXFile(XFile* file) +
Save the object to a file pointer (not the options) +

+ + +

ovoid addCmdOption(CmdOption* option) +
Add an option to the command line. Use this method +if the wrappers that are provided are not sufficient. +

+ + +

ovoid writeLog(XFile* file, bool write_associated_files) +
Write a log in file. +If desired, the associated files can be printed. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdOption

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/CmdOption.html b/torch3/manual/CmdOption.html new file mode 100644 index 0000000..47f60e8 --- /dev/null +++ b/torch3/manual/CmdOption.html @@ -0,0 +1,211 @@ + + + + + class CmdOption + + + + +

class CmdOption

This class defines an option for the command line.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]char* name +
Name of the option +
+[more]char* type_name +
Type name of the option +
+[more]char* help +
An help string. +
+[more]bool save +
True is the option has to be saved when saving the command line +
+[more]bool is_setted +
True is the option has been setted after reading the command-line +

+ +

+

Public Methods

+[more] CmdOption(const char* name_, const char* type_name_, const char* help_="", bool save_=false) +
+[more]virtual void initValue() +
Initialize the value of the option +
+[more]virtual void printValue(XFile* file_) +
If is_setted is true, print the current value, else the init value +
+[more]virtual void read(int* argc_, char*** argv_) +
Read the option on the command line. +
+[more]bool isOption(bool set_=false) +
Returns true if it's an optional argument. +
+[more]bool isArgument(bool set_=false) +
Returns true if it's a required argument. +
+[more]bool isText(bool set_=false) +
Returns true if it's just text to be displayed in the command line. +
+[more]bool isMasterSwitch(bool set_=false) +
Returns true if it's a master switch. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class defines an option for the command line. +If you need special command line arguments/options, +you have to create a new children of this class. + +

+
+ + + +
ochar* name +
Name of the option +

+ + +

ochar* type_name +
Type name of the option +

+ + +

ochar* help +
An help string. +Cannot be NULL. +

+ + +

obool save +
True is the option has to be saved +when saving the command line +

+ + +

obool is_setted +
True is the option has been setted after +reading the command-line +

+ + +

o CmdOption(const char* name_, const char* type_name_, const char* help_="", bool save_=false) +

+ + +

ovirtual void initValue() +
Initialize the value of the option +

+ + +

ovirtual void printValue(XFile* file_) +
If is_setted is true, print the current value, else the init value +

+ + +

ovirtual void read(int* argc_, char*** argv_) +
Read the option on the command line. +argv_ and argc_ have to point of the next +option after that. +

+ + +

obool isOption(bool set_=false) +
Returns true if it's an optional argument. +If set_ is true, set it to an optional argument. +

+ + +

obool isArgument(bool set_=false) +
Returns true if it's a required argument. +If set_ is true, set it to a required argument. +

+ + +

obool isText(bool set_=false) +
Returns true if it's just text to be displayed in the command line. +If set_ is true, set it to text mode. +

+ + +

obool isMasterSwitch(bool set_=false) +
Returns true if it's a master switch. +If set_ is true, set it to a master switch. +

+
+
Direct child classes: +
StringCmdOption
+RealCmdOption
+IntCmdOption
+FileListCmdOption
+BoolCmdOption
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Collectionofmatrixfactorisationoperationfunctions..html b/torch3/manual/Collectionofmatrixfactorisationoperationfunctions..html new file mode 100644 index 0000000..f20f3a1 --- /dev/null +++ b/torch3/manual/Collectionofmatrixfactorisationoperationfunctions..html @@ -0,0 +1,52 @@ + + + + + Collection of matrix factorisation operation functions. + + + + +

Collection of matrix factorisation operation functions.

+
+

+
+void mxLUFactor(Mat* mat, Perm* pivot) +
Gaussian elimination with scaled partial pivoting. +
+void mxLUSolve(Mat* mat, Perm* pivot, Vec* b, Vec* x) +
Given an LU factorisation in A, solve Ax=b +
+void mxLUTSolve(Mat* mat, Perm* pivot, Vec* b, Vec* x) +
Given an LU factorisation in A, solve A^Tx=b +
+void mxInverse(Mat* mat, Mat* out) +
Returns inverse of A, provided A is not too rank deficient. +
+void mxSolve(Mat* mat, Vec* b, Vec* x) +
Given A and b, solve Ax=b +

+ + + +
+

Documentation

+
Collection of matrix factorisation operation functions. +Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

Most matrix factorisation routines are in-situ +unless otherwise specified. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Collectionofmatrixoperationfunctions..html b/torch3/manual/Collectionofmatrixoperationfunctions..html new file mode 100644 index 0000000..4c9bc9c --- /dev/null +++ b/torch3/manual/Collectionofmatrixoperationfunctions..html @@ -0,0 +1,76 @@ + + + + + Collection of matrix operation functions. + + + + +

Collection of matrix operation functions.

+
+

+
+void mxMatAddMat(Mat* mat1, Mat* mat2, Mat* out) +
Matrix addition -- may be in-situ +
+void mxMatSubMat(Mat* mat1, Mat* mat2, Mat* out) +
Matrix subtraction -- may be in-situ +
+void mxMatMulMat(Mat* mat1, Mat* mat2, Mat* out) +
Matrix-matrix multiplication +
+void mxMatMulTrMat(Mat* mat1, Mat* mat2, Mat* out) +
Matrix-matrix transposed multiplication. +
+void mxTrMatMulMat(Mat* mat1, Mat* mat2, Mat* out) +
Matrix transposed-matrix multiplication. +
+void mxMatMulVec(Mat* mat, Vec* b, Vec* out) +
Matrix-vector multiplication. +
+void mxRealMulMat(real scalar, Mat* matrix, Mat* out) +
Scalar-matrix multiply -- may be in-situ +
+void mxVecMulMat(Vec* b, Mat* mat, Vec* out) +
Vector-matrix multiplication. +
+void mxTrMat(Mat* in, Mat* out) +
Transpose matrix +
+void mxSwapRowsMat(Mat* mat, int i, int j, int lo, int hi) +
Swaps rows i and j of matrix A upto column lim. +
+void mxSwapColsMat(Mat* mat, int i, int j, int lo, int hi) +
Swap columns i and j of matrix A upto row lim. +
+void mxMatAddRealMulMat(Mat* mat1, Mat* mat2, real s, Mat* out) +
Matrix-scalar multiply and add. +
+void mxVecAddRealMulMatMulVec(Vec* v1, real alpha, Mat* mat, Vec* v2, Vec* out) +
Matrix-vector multiply and add. +
+void mxVecAddRealMulVecMulMat(Vec* v1, real alpha, Vec* v2, Mat* mat, Vec* out) +
Vector-matrix multiply and add -- may not be in situ -- returns out' == v1' + alpha * v2'*A +

+ + + +
+

Documentation

+
Collection of matrix operation functions. +Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Collectionofpermutationsoperationfunctions..html b/torch3/manual/Collectionofpermutationsoperationfunctions..html new file mode 100644 index 0000000..707f130 --- /dev/null +++ b/torch3/manual/Collectionofpermutationsoperationfunctions..html @@ -0,0 +1,55 @@ + + + + + Collection of permutations operation functions. + + + + +

Collection of permutations operation functions.

+
+

+
+void mxPermInv(Perm* px, Perm* out) +
Invert permutation -- in situ. +
+void mxPermMulPerm(Perm* px1, Perm* px2, Perm* out) +
Permutation multiplication (composition) -- not in-situ +
+void mxPermVec(Perm* px, Vec* vec, Vec* out) +
Permute vector -- can be in-situ +
+void mxPermInvVec(Perm* px, Vec* x, Vec* out) +
Apply the inverse of px to x, returning the result in out. +
+void mxTrPerm(Perm* px, int i1, int i2) +
Transpose elements of permutation. +
+void mxPermColsMat(Perm* px, Mat* mat, Mat* out) +
Permute columns of matrix A; out = Apx'. +
+void mxPermRowsMat(Perm* px, Mat* mat, Mat* out) +
Permute rows of matrix A; out = pxA. +

+ + + +
+

Documentation

+
Collection of permutations operation functions. +Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ConnectedMachine.html b/torch3/manual/ConnectedMachine.html new file mode 100644 index 0000000..d945cb2 --- /dev/null +++ b/torch3/manual/ConnectedMachine.html @@ -0,0 +1,198 @@ + + + + + class ConnectedMachine + + + + +

class ConnectedMachine

Easy connections between several GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] ConnectedMachine() +
+[more]void addFCL(GradientMachine* machine) +
Add a Full Connected Layer. +
+[more]void addMachine(GradientMachine* machine) +
Add a machine on the current layer +
+[more]void connectOn(GradientMachine* machine) +
Connect the last added machine on machine. +
+[more]void addLayer() +
Add a layer (you don't have to call that for the first layer) +
+[more]void build() +
Contruct the machine. +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Easy connections between several GradientMachine. +GradientMachine has "layers" on which you can +add some GradientMachine. + +

The inputs of the machine on the first layer will +be the inputs of the ConnectedMachine. + +

The outputs of the ConnectedMachine are the union +(in the order of adding) of all machines on the +last layer. + +

+
+ + + +
o ConnectedMachine() +

+ + +

ovoid addFCL(GradientMachine* machine) +
Add a Full Connected Layer. The machine is fully connected +to the previous layer. If necessary, a layer is added before +adding the machine. +

+ + +

ovoid addMachine(GradientMachine* machine) +
Add a machine on the current layer +

+ + +

ovoid connectOn(GradientMachine* machine) +
Connect the last added machine on machine. +Note that machine must be in a previous layer. +

+ + +

ovoid addLayer() +
Add a layer (you don't have to call that for the first layer) +

+ + +

ovoid build() +
Contruct the machine. you need to call that after adding and +connecting all the machines. +

+
+
Direct child classes: +
SpeechMLP
+MLP
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Criterion.html b/torch3/manual/Criterion.html new file mode 100644 index 0000000..09060f0 --- /dev/null +++ b/torch3/manual/Criterion.html @@ -0,0 +1,179 @@ + + + + + class Criterion + + + + +

class Criterion

Criterion class for StochasticGradient.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]DataSet* data +
DataSet used to compute the error +

+ +

+

Public Methods

+[more] Criterion(int n_inputs_, int n_params_=0) +
+[more]virtual void setDataSet(DataSet* data_) +
Set data to data_. +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Criterion class for StochasticGradient. +A Criterion computes an error with its inputs +and a dataset data. + +

It knows how to backpropagate this error. + +

A Criterion shouldn't be connected to the inputs of +another GradientMachine. +ne doit pas se connecter sur l'entree d'une + +

By default, the number of outputs for a Criterion +is fixed to one. It must contain the error: +This one is used by the StochasticGradient for the +stopping criterion. + +

+
+ + + +
oDataSet* data +
DataSet used to compute the error +

+ + +

o Criterion(int n_inputs_, int n_params_=0) +

+ + +

ovirtual void setDataSet(DataSet* data_) +
Set data to data_. The criterion +should be able to react to this function. +

+
+
Direct child classes: +
WeightedMSECriterion
+NLLCriterion
+MultiCriterion
+MSECriterion
+ClassNLLCriterion
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DataSet.html b/torch3/manual/DataSet.html new file mode 100644 index 0000000..7e39ba1 --- /dev/null +++ b/torch3/manual/DataSet.html @@ -0,0 +1,281 @@ + + + + + class DataSet + + + + +

class DataSet

Provides an interface to manipulate all kind of data.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int* selected_examples +
The indices of all selected examples. +
+[more]int n_inputs +
Frame size of inputs. +
+[more]int n_targets +
Frame size of targets. +
+[more]int real_current_example_index +
Index of the current example. +
+[more]Sequence* inputs +
Pointer on the inputs of the current example +
+[more]Sequence* targets +
Pointer to the targets of the current example +
+[more]int n_examples +
Number of examples in the dataset. +
+[more]int n_real_examples +
Real number of examples in the dataset. +

+ +

+

Public Methods

+[more] DataSet() +
+[more]void init(int n_examples_, int n_inputs_, int n_targets_) +
Method which initializes some fields of the datasets. +
+[more]void setExample(int t, bool set_inputs=true, bool set_targets=true) +
Set targets and inputs to the targets and inputs of the example with the index selected_examples[t]. +
+[more]virtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) = 0 +
Set targets and inputs to the targets and inputs of the example with the index t. +
+[more]virtual void pushSubset(int* subset_, int n_examples_) +
Set a new subset. +
+[more]virtual void popSubset() +
Remove the last subset. +
+[more]virtual void pushExample() = 0 +
Tells that the current example must be kept in memory after next calls of setExample(). +
+[more]virtual void popExample() = 0 +
Tells that the last pushed example will be now the current example, and therefore, will be forgeted after the next call of setExample(). +
+[more]virtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) = 0 +
Put in n_input_frames and n_target_frames the number of input frames and target frames for example t. +
+[more]virtual void preProcess(PreProcessing* pre_processing) = 0 +
Perform some pre-processing on data +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Provides an interface to manipulate all kind of data. +A dataset contains two kind of things: inputs sequences +and targets sequences. + +

+
+ + + +
oint* selected_examples +
The indices of all selected examples. +When select_examples is false, it contains +the indices of all examples. +

+ + +

oint n_inputs +
Frame size of inputs. +

+ + +

oint n_targets +
Frame size of targets. +

+ + +

oint real_current_example_index +
Index of the current example. +Warning: it's the real index and not the index +in the selected_examples table. +

+ + +

oSequence* inputs +
Pointer on the inputs of the current example +

+ + +

oSequence* targets +
Pointer to the targets of the current example +

+ + +

oint n_examples +
Number of examples in the dataset. +If you're using select_examples, it's +the number of selected examples. +

+ + +

oint n_real_examples +
Real number of examples in the dataset. +It's the number of examples in memory. +(= n_examples if select_examples is false) +

+ + +

o DataSet() +

+ + +

ovoid init(int n_examples_, int n_inputs_, int n_targets_) +
Method which initializes some fields of the datasets. +It has to be called only in the constructor of your subclasses. +Just for developpers of new datasets. +

+ + +

ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
Set targets and inputs to the targets and inputs +of the example with the index selected_examples[t]. +Warning: after a setExample() the previous selected example +is not supposed to exist... for that, use pushExample(). +

+ + +

ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) = 0 +
Set targets and inputs to the targets and inputs +of the example with the index t. If you create a new +dataset, you must update inside current_example_index. +Warning: after a setExample() the previous selected example +is not supposed to exist... for that, use pushExample(). +

+ + +

ovirtual void pushSubset(int* subset_, int n_examples_) +
Set a new subset. +
    +
  • subset_ (of size n_examples_) is a set +of indices which define a subset of data. +
  • if a pushSubset() has been already called, +the next pushSubset() defines a subset of the +previous subset, and so on... +
  • this function set select_examples to true +and set the read indices of the examples in +selected_examples. +
+

+ + +

ovirtual void popSubset() +
Remove the last subset. +
    +
  • recomputes "selected_examples". +
  • if it was the last subset, set select_examples +to false. +
+

+ + +

ovirtual void pushExample() = 0 +
Tells that the current example must be kept in memory +after next calls of setExample(). +

+ + +

ovirtual void popExample() = 0 +
Tells that the last pushed example will be now the current +example, and therefore, will be forgeted after the next +call of setExample(). +

+ + +

ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) = 0 +
Put in n_input_frames and n_target_frames the number +of input frames and target frames for example t. +This take subsets in account. +If one field is NULL, it will not be returned. +

+ + +

ovirtual void preProcess(PreProcessing* pre_processing) = 0 +
Perform some pre-processing on data +

+
+
Direct child classes: +
MemoryDataSet
+FrameSelectorDataSet
+ExampleFrameSelectorDataSet
+DiskDataSet
+ClassFormatDataSet
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DecoderBatchTest.html b/torch3/manual/DecoderBatchTest.html new file mode 100644 index 0000000..263dfc9 --- /dev/null +++ b/torch3/manual/DecoderBatchTest.html @@ -0,0 +1,188 @@ + + + + + class DecoderBatchTest + + + + +

class DecoderBatchTest

This class is used to decode a set of test files and display statistics and results for each file (ie.
+
+ +
+

+

Public Methods

+[more]void run() +
Runs the batch test according to the options set by the call to 'configure' +

+ +

+

Public Members

+[more] Configures the batch test +
+[more] 'datafiles_filename' is the file containing a list of the input data files +
+[more] that need to be decoded. +
+[more] will occur in the order the files are listed in this file +
+[more] 'expected_results_file' is the file containing the correct transcriptions +
+[more] for all input data files. +
+[more] the same as the order in 'datafiles_filename' +
+[more] 'decoder_' is a pointer to the decoder to be used to perform the recognition +
+[more] 'remove_sil' indicates whether the silence word is to be removed from the +
+[more] recognition results before statistics are calculated +
+[more] 'output_res' indicates whether the result of each recognition is to be output +
+[more] immediately after it is obtained +
+[more] 'preload_data' indicates whether all of the input data in all files is to be +
+[more] preloaded into memory before any decoding occurs (takes lots of memory and lots +
+[more] of time before any results are obtained if the number of input data files +
+[more] is large +
+[more] 'pre_calc_emission_probs' indicates whether emission probabilities for +
+[more] all input files are to be calculated before the decoder is invoked. +
+[more] Intended to be called after the 'run' method has returned. +
+[more] recognition results for all input data files and compiles insertions, +

+ +
+ + +
+

Documentation

+
This class is used to decode a set of test files and display statistics and results +for each file (ie. expected and actual words recognised) and also for the entire +test set (ie. insertions, deletions, substitutions, accuracy, total time). + +

+
+ + + +
o Configures the batch test +
Configures the batch test +

+ + +

o 'datafiles_filename' is the file containing a list of the input data files +
'datafiles_filename' is the file containing a list of the input data files +

+ + +

o that need to be decoded. +
that need to be decoded. Absolute pathnames are required. The decoding +

+ + +

o will occur in the order the files are listed in this file +
will occur in the order the files are listed in this file +

+ + +

o 'expected_results_file' is the file containing the correct transcriptions +
'expected_results_file' is the file containing the correct transcriptions +

+ + +

o for all input data files. +
for all input data files. The ordering of the files does not have to be +

+ + +

o the same as the order in 'datafiles_filename' +
the same as the order in 'datafiles_filename' +

+ + +

o 'decoder_' is a pointer to the decoder to be used to perform the recognition +
'decoder_' is a pointer to the decoder to be used to perform the recognition +

+ + +

o 'remove_sil' indicates whether the silence word is to be removed from the +
'remove_sil' indicates whether the silence word is to be removed from the +

+ + +

o recognition results before statistics are calculated +
recognition results before statistics are calculated +

+ + +

o 'output_res' indicates whether the result of each recognition is to be output +
'output_res' indicates whether the result of each recognition is to be output +

+ + +

o immediately after it is obtained +
immediately after it is obtained +

+ + +

o 'preload_data' indicates whether all of the input data in all files is to be +
'preload_data' indicates whether all of the input data in all files is to be +

+ + +

o preloaded into memory before any decoding occurs (takes lots of memory and lots +
preloaded into memory before any decoding occurs (takes lots of memory and lots +

+ + +

o of time before any results are obtained if the number of input data files +
of time before any results are obtained if the number of input data files +

+ + +

o is large +
is large +

+ + +

o 'pre_calc_emission_probs' indicates whether emission probabilities for +
'pre_calc_emission_probs' indicates whether emission probabilities for +

+ + +

o all input files are to be calculated before the decoder is invoked. +
all input files are to be calculated before the decoder is invoked. This +

+ + +

o Intended to be called after the 'run' method has returned. +
Intended to be called after the 'run' method has returned. Processes the +

+ + +

o recognition results for all input data files and compiles insertions, +
recognition results for all input data files and compiles insertions, +

+ + +

ovoid run() +
Runs the batch test according to the options set by the call to 'configure' +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DecoderSingleTest.html b/torch3/manual/DecoderSingleTest.html new file mode 100644 index 0000000..2ce39a5 --- /dev/null +++ b/torch3/manual/DecoderSingleTest.html @@ -0,0 +1,251 @@ + + + + + class DecoderSingleTest + + + + +

class DecoderSingleTest

This class is used to recognise a single input data file, post-process the recognition result and output the result.
+
+ +
+

+

Public Methods

+[more]void removeSentMarksFromActual( Vocabulary* vocabulary ) +
Internal functions +

+ +

+

Public Members

+[more] Configures the test +
+[more] 'test_id_' is an ID assigned to this particular test +
+[more] 'test_filename_' is the absolute pathname of the input data file +
+[more] 'n_expected_words_' and 'expected_words_' contain information about +
+[more] the expected result of the test (ie. +
+[more] 'data_format_' indicates the type of data contained in the input +
+[more] data file. +
+[more] 'phone_models_' is a pointer to the PhoneModels instance that contains +
+[more] the phone HMM's. +
+[more] data (eg. +
+[more] 'remove_sent_marks_' indicates whether the sentence start and end +
+[more] words in the recognition result are to be removed +
+[more] 'output_result_' indicates whether the recognition result is to be +
+[more] output after the decoding has occurred +
+[more] 'out_fd' is the file where output will be written (if NULL then +
+[more] stdout assumed) +
+[more] 'output_ctm_' indicates if the output is to be in CTM format +
+[more] 'frame_msec_step_size' is the frame step size in milliseconds and is +
+[more] Configures the test. +
+[more] in a big archive file +
+[more] Parameters are same as other 'configure' method except 'test_filename_' +
+[more] has been replaced by 'archive_offset_' +
+[more] 'archive_offset' is the offset into an archive input file where the +
+[more] Runs the tests using the recogniser pointed to by 'decoder' +
+[more] 'archive_fd' is the big file containing the input data. +
+[more] this is not NULL, the archive_offset member variable is used +
+[more] Outputs the recognition result. +
+[more] recognition result (ie. +
+[more] strings and displayed. +

+ +
+ + +
+

Documentation

+
This class is used to recognise a single input data file, post-process the +recognition result and output the result. The DecoderBatchTest class +contains of an array of these objects. + +

+
+ + + +
o Configures the test +
Configures the test +

+ + +

o 'test_id_' is an ID assigned to this particular test +
'test_id_' is an ID assigned to this particular test +

+ + +

o 'test_filename_' is the absolute pathname of the input data file +
'test_filename_' is the absolute pathname of the input data file +

+ + +

o 'n_expected_words_' and 'expected_words_' contain information about +
'n_expected_words_' and 'expected_words_' contain information about +

+ + +

o the expected result of the test (ie. +
the expected result of the test (ie. the correct transcription). +

+ + +

o 'data_format_' indicates the type of data contained in the input +
'data_format_' indicates the type of data contained in the input +

+ + +

o data file. +
data file. Only 1 input data format has been implemented so far. +

+ + +

o 'phone_models_' is a pointer to the PhoneModels instance that contains +
'phone_models_' is a pointer to the PhoneModels instance that contains +

+ + +

o the phone HMM's. +
the phone HMM's. This used to verify that datafiles contain expected +

+ + +

o data (eg. +
data (eg. emission probs or features, correct vector sizes) +

+ + +

o 'remove_sent_marks_' indicates whether the sentence start and end +
'remove_sent_marks_' indicates whether the sentence start and end +

+ + +

o words in the recognition result are to be removed +
words in the recognition result are to be removed +

+ + +

o 'output_result_' indicates whether the recognition result is to be +
'output_result_' indicates whether the recognition result is to be +

+ + +

o output after the decoding has occurred +
output after the decoding has occurred +

+ + +

o 'out_fd' is the file where output will be written (if NULL then +
'out_fd' is the file where output will be written (if NULL then +

+ + +

o stdout assumed) +
stdout assumed) +

+ + +

o 'output_ctm_' indicates if the output is to be in CTM format +
'output_ctm_' indicates if the output is to be in CTM format +

+ + +

o 'frame_msec_step_size' is the frame step size in milliseconds and is +
'frame_msec_step_size' is the frame step size in milliseconds and is +

+ + +

o Configures the test. +
Configures the test. This version is used when we have input data +

+ + +

o in a big archive file +
in a big archive file +

+ + +

o Parameters are same as other 'configure' method except 'test_filename_' +
Parameters are same as other 'configure' method except 'test_filename_' +

+ + +

o has been replaced by 'archive_offset_' +
has been replaced by 'archive_offset_' +

+ + +

o 'archive_offset' is the offset into an archive input file where the +
'archive_offset' is the offset into an archive input file where the +

+ + +

o Runs the tests using the recogniser pointed to by 'decoder' +
Runs the tests using the recogniser pointed to by 'decoder' +

+ + +

o 'archive_fd' is the big file containing the input data. +
'archive_fd' is the big file containing the input data. When +

+ + +

o this is not NULL, the archive_offset member variable is used +
this is not NULL, the archive_offset member variable is used +

+ + +

o Outputs the recognition result. +
Outputs the recognition result. If 'vocab' is defined, then the +

+ + +

o recognition result (ie. +
recognition result (ie. vocab entry indices) are converted to +

+ + +

o strings and displayed. +
strings and displayed. If 'vocab' is NULL then the indices are +

+ + +

ovoid removeSentMarksFromActual( Vocabulary* vocabulary ) +
Internal functions +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DecodingHMM.html b/torch3/manual/DecodingHMM.html new file mode 100644 index 0000000..4b1baf2 --- /dev/null +++ b/torch3/manual/DecodingHMM.html @@ -0,0 +1,93 @@ + + + + + class DecodingHMM + + + + +

class DecodingHMM

This class contains all HMM information required for decoding.
+
+ +
+

+

Public Methods

+[more]void mergeModels( int n_models, DecodingHMM** models ) +
Internal function to merge component models into a big HMM +
+[more]void setupSuccessorStates( DecodingHMMState* state, short n_successors_, short* sucessor_states_, real* log_trans_probs_ ) +
Configures successor state information for the state denoted by 'state' +

+ +

+

Public Members

+[more] Converts a Torch HMM instance to a DecodingHMM representation. +
+[more] class contains a lot of member variables used in training that are not +
+[more] Concatenates all elements in the array of DecodingHMM instances into a single +
+[more] Creates a DecodingHMM using the distributions in 'states_' and the log +
+[more] Initialises the state denoted by 'state' with a Distribution and +

+ +
+ + +
+

Documentation

+
This class contains all HMM information required for decoding. Most information +is embedded in the states themselves (DecodingHMMState structures). The DecodingHMM +can be created a number of ways to facilitate compatibility with the Torch HMM class +and to allow easy concatenation of models (eg. when constructing word models from +phoneme models). + +

+
+ + + +
o Converts a Torch HMM instance to a DecodingHMM representation. +
Converts a Torch HMM instance to a DecodingHMM representation. The Torch HMM +

+ + +

o class contains a lot of member variables used in training that are not +
class contains a lot of member variables used in training that are not +

+ + +

o Concatenates all elements in the array of DecodingHMM instances into a single +
Concatenates all elements in the array of DecodingHMM instances into a single +

+ + +

o Creates a DecodingHMM using the distributions in 'states_' and the log +
Creates a DecodingHMM using the distributions in 'states_' and the log +

+ + +

ovoid mergeModels( int n_models, DecodingHMM** models ) +
Internal function to merge component models into a big HMM +

+ + +

ovoid setupSuccessorStates( DecodingHMMState* state, short n_successors_, short* sucessor_states_, real* log_trans_probs_ ) +
Configures successor state information for the state denoted by 'state' +

+ + +

o Initialises the state denoted by 'state' with a Distribution and +
Initialises the state denoted by 'state' with a Distribution and +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DecodingHypothesis.html b/torch3/manual/DecodingHypothesis.html new file mode 100644 index 0000000..672f6f9 --- /dev/null +++ b/torch3/manual/DecodingHypothesis.html @@ -0,0 +1,73 @@ + + + + + class DecodingHypothesis + + + + +

class DecodingHypothesis

This class contains all hypothesis data that needs to be updated and propagated as hypotheses are extended through word models and across word boundaries.
+
+ +
+

+

Public Members

+[more] Unlinks this instance from its word_level_info member variable +
+[more] If this instance was the only entity connected to the +
+[more] word_level_info object, then the word_level_info object is +
+[more] Updates the hypothesis information when a word boundary +
+[more] Updates the hypothesis information when a word-interior state +

+ +
+ + +
+

Documentation

+
This class contains all hypothesis data that needs to be updated +and propagated as hypotheses are extended through word models and +across word boundaries. Methods are provided to transfer data +between DecodingHypothesis objects in varying ways. + +

+
+ + + +
o Unlinks this instance from its word_level_info member variable +
Unlinks this instance from its word_level_info member variable +

+ + +

o If this instance was the only entity connected to the +
If this instance was the only entity connected to the +

+ + +

o word_level_info object, then the word_level_info object is +
word_level_info object, then the word_level_info object is +

+ + +

o Updates the hypothesis information when a word boundary +
Updates the hypothesis information when a word boundary +

+ + +

o Updates the hypothesis information when a word-interior state +
Updates the hypothesis information when a word-interior state +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DiagonalGMM.html b/torch3/manual/DiagonalGMM.html new file mode 100644 index 0000000..6bab864 --- /dev/null +++ b/torch3/manual/DiagonalGMM.html @@ -0,0 +1,420 @@ + + + + + class DiagonalGMM + + + + +

class DiagonalGMM

This class can be used to model Diagonal Gaussian Mixture Models.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_gaussians +
number of Gaussians in the mixture +
+[more]real prior_weights +
prior weights of the Gaussians, used in EM to give a small prior on each Gaussian +
+[more]EMTrainer* initial_kmeans_trainer +
optional initializations if nothing is given, then random calling by reset(), at your own risks or model loaded by the user. +
+[more]MeasurerList* initial_kmeans_trainer_measurers +
as well as a measurer of this trainer +
+[more]real* log_weights +
the pointers to the parameters +
+[more]real* dlog_weights +
the pointers to the derivative of the parameters +
+[more]real* var_threshold +
this contains the minimal value of each variance +
+[more]Sequence* log_probabilities_g +
for each frame, for each gaussian, keep its log probability +
+[more]int best_gauss +
gaussian that maximize the observed frame +
+[more]Sequence* best_gauss_per_frame +
gaussian that maximize the observed frame +
+[more]real* sum_log_var_plus_n_obs_log_2_pi +
in order to faster the computation, we can do some "pre-computation" pre-computed sum_log_var + n_obs * log_2_pi +
+[more]real** minus_half_over_var +
pre-computed -05 / var +
+[more]real** means_acc +
accumulators for EM +

+ +

+

Public Methods

+[more] DiagonalGMM(int n_inputs_, int n_gaussians_, EMTrainer* initial_kmeans_trainer_ = NULL) +
+[more]virtual void reset() +
This methods have to call by the user to initialized the random parameters +
+[more]virtual void setDataSet(DataSet* data_) +
If the KmeanTrainer has been given to the constructor, Kmeans algorithm is perform +
+[more]virtual void setVarThreshold(real* var_threshold_) +
Set the minimum value for the variances +
+[more]virtual void eMIterInitialize() +
Methods used to initialize the model at the beginning of each EM iteration +
+[more]virtual void iterInitialize() +
Methods used to initialize the model at the beginning of each gradient descent iteration +
+[more]virtual real frameLogProbability(int t, real* inputs) +
Returns the log probability of a frame of a sequence +
+[more]virtual real viterbiFrameLogProbability(int t, real* inputs) +
Returns the log probability of a frame of a sequence on viterbi mode +
+[more]virtual real frameLogProbabilityOneGaussian(int g, real* inputs) +
this method returns the log probability of the "g" Gaussian +
+[more]virtual void sequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each example during gradient descent training +
+[more]virtual void eMSequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each example during EM training +
+[more]virtual void frameEMAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of EM for a frame +
+[more]virtual void frameViterbiAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of Viterbi for a frame +
+[more]virtual void eMUpdate() +
The update after each iteration for EM +
+[more]virtual void update() +
The update after each iteration for gradient +
+[more]virtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Same as backward, but for one frame only +
+[more]virtual void frameDecision(int t, real* decision) +
Returns the expected value in decision +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to model Diagonal Gaussian Mixture Models. +They can be trained using either EM (with EMTrainer) or gradient descent +(with GMTrainer). + +

+
+ + + +
oint n_gaussians +
number of Gaussians in the mixture +

+ + +

oreal prior_weights +
prior weights of the Gaussians, used in EM to give +a small prior on each Gaussian +

+ + +

oEMTrainer* initial_kmeans_trainer +
optional initializations +if nothing is given, then random calling by reset(), +at your own risks or model loaded by the user. +one can give a initial trainer containing a kmeans +

+ + +

oMeasurerList* initial_kmeans_trainer_measurers +
as well as a measurer of this trainer +

+ + +

oreal* log_weights +
the pointers to the parameters +

+ + +

oreal* dlog_weights +
the pointers to the derivative of the parameters +

+ + +

oreal* var_threshold +
this contains the minimal value of each variance +

+ + +

oSequence* log_probabilities_g +
for each frame, for each gaussian, keep its log probability +

+ + +

oint best_gauss +
gaussian that maximize the observed frame +

+ + +

oSequence* best_gauss_per_frame +
gaussian that maximize the observed frame +

+ + +

oreal* sum_log_var_plus_n_obs_log_2_pi +
in order to faster the computation, we can do some "pre-computation" +pre-computed sum_log_var + n_obs * log_2_pi +

+ + +

oreal** minus_half_over_var +
pre-computed -05 / var +

+ + +

oreal** means_acc +
accumulators for EM +

+ + +

o DiagonalGMM(int n_inputs_, int n_gaussians_, EMTrainer* initial_kmeans_trainer_ = NULL) +

+ + +

ovirtual void reset() +
+This methods have to call by the user to initialized the +random parameters +

+ + +

ovirtual void setDataSet(DataSet* data_) +
+If the KmeanTrainer has been given to the constructor, Kmeans algorithm +is perform +

+ + +

ovirtual void setVarThreshold(real* var_threshold_) +
+Set the minimum value for the variances +

+ + +

ovirtual void eMIterInitialize() +
Methods used to initialize the model at the beginning of each +EM iteration +

+ + +

ovirtual void iterInitialize() +
Methods used to initialize the model at the beginning of each +gradient descent iteration +

+ + +

ovirtual real frameLogProbability(int t, real* inputs) +
Returns the log probability of a frame of a sequence +

+ + +

ovirtual real viterbiFrameLogProbability(int t, real* inputs) +
Returns the log probability of a frame of a sequence on viterbi mode +

+ + +

ovirtual real frameLogProbabilityOneGaussian(int g, real* inputs) +
this method returns the log probability of the "g" Gaussian +

+ + +

ovirtual void sequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each +example during gradient descent training +

+ + +

ovirtual void eMSequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each +example during EM training +

+ + +

ovirtual void frameEMAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of EM for a frame +

+ + +

ovirtual void frameViterbiAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of Viterbi for a frame +

+ + +

ovirtual void eMUpdate() +
The update after each iteration for EM +

+ + +

ovirtual void update() +
The update after each iteration for gradient +

+ + +

ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Same as backward, but for one frame only +

+ + +

ovirtual void frameDecision(int t, real* decision) +
Returns the expected value in decision +

+
+
Direct child classes: +
MAPDiagonalGMM
+KMeans
+
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DiskDataSet.html b/torch3/manual/DiskDataSet.html new file mode 100644 index 0000000..a4ef513 --- /dev/null +++ b/torch3/manual/DiskDataSet.html @@ -0,0 +1,184 @@ + + + + + class DiskDataSet + + + + +

class DiskDataSet

Provides an interface to manipulate all kind of data which are kept on disk, and not fully loaded in memory.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]PreProcessingList* pre_processes +
List if pre processes to do +
+[more]IOSequence* io_inputs +
IOMatrix which provides inputs +
+[more]IOSequence* io_targets +
IOMatrix which provides targets +

+ +

+

Public Methods

+[more] DiskDataSet() +
+[more]void init(IOSequence* io_inputs_, IOSequence* io_targets_) +
This function has to be called by your sub-classes. +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Provides an interface to manipulate all kind of data which are +kept on disk, and not fully loaded in memory. +It uses IOSequence. +Usefull for large databases. +DiskMatDataSet is a good example if you plan to code a new DiskDataSet. + +

+
+ + + +
oPreProcessingList* pre_processes +
List if pre processes to do +

+ + +

oIOSequence* io_inputs +
IOMatrix which provides inputs +

+ + +

oIOSequence* io_targets +
IOMatrix which provides targets +

+ + +

o DiskDataSet() +

+ + +

ovoid init(IOSequence* io_inputs_, IOSequence* io_targets_) +
This function has to be called by your sub-classes. +You give here the IOMatrix which handle the inputs +and the targets of your dataset. +Should be called in the constructor of all yoyr sub-classes. +

+
+
Direct child classes: +
DiskMatDataSet
+DiskHTKDataSet
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
DiskMatDataSet +
IOSequence +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DiskHTKDataSet.html b/torch3/manual/DiskHTKDataSet.html new file mode 100644 index 0000000..bf35a57 --- /dev/null +++ b/torch3/manual/DiskHTKDataSet.html @@ -0,0 +1,146 @@ + + + + + class DiskHTKDataSet + + + + +

class DiskHTKDataSet

Provides an interface to manipulate HTK data which are kept on disk, and not fully loaded in memory.
+
+ +

Inheritance:

+ + + + + + + +

Inherited from DiskDataSet:

+
+

+

Public Fields

+oPreProcessingList* pre_processes +
+oIOSequence* io_inputs +
+oIOSequence* io_targets +

+ +

+

Public Methods

+ovoid init(IOSequence* io_inputs_, IOSequence* io_targets_) +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Provides an interface to manipulate HTK data which are +kept on disk, and not fully loaded in memory. +It uses IOSequence. +Usefull for large databases. + +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +
See Also:
DiskMatDataSet +
IOSequence +
IOHTK +
IOHTKTarget +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DiskMatDataSet.html b/torch3/manual/DiskMatDataSet.html new file mode 100644 index 0000000..d3adc9d --- /dev/null +++ b/torch3/manual/DiskMatDataSet.html @@ -0,0 +1,185 @@ + + + + + class DiskMatDataSet + + + + +

class DiskMatDataSet

Matrix DataSet On Disk.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] DiskMatDataSet(const char* filename, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Create a new dataset from the file filename. +
+[more] DiskMatDataSet(char** filenames, int n_files_, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Same as the previous constructor, but for several files. +
+[more] DiskMatDataSet(char** input_filenames, char** target_filenames, int n_files_, int max_load=-1, bool binary_mode=false) +
Here the inputs and the targets are in separated files. +

+ +
+

Inherited from DiskDataSet:

+
+

+

Public Fields

+oPreProcessingList* pre_processes +
+oIOSequence* io_inputs +
+oIOSequence* io_targets +

+ +

+

Public Methods

+ovoid init(IOSequence* io_inputs_, IOSequence* io_targets_) +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Matrix DataSet On Disk. +The standard dataset, with data not fully loaded in memory. +Usefull for large databases. + +

+
+ + + +
o DiskMatDataSet(const char* filename, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Create a new dataset from the file filename. If the file contains only one sequence, set one_file_is_one_sequence +to true. If there is several sequences, and you want only to load the first n ones, set max_load to n (else max_load +should be a negative number). If binary_mode is true, the IOBin format will be used, else it will be the IOAscii format. + +

Input and target sequence will have the same number of frames. For each frame given by the dataset, the first n_inputs_ +real are for the inputs and then the next n_targets_ real are for the targets. (n_inputs_ is the input frame size and +n_targets_ is the target frame size). +

+ + +

o DiskMatDataSet(char** filenames, int n_files_, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Same as the previous constructor, but for several files. If one_file_is_one_sequence is true, each files will be considered as they +had only one sequence. +

+ + +

o DiskMatDataSet(char** input_filenames, char** target_filenames, int n_files_, int max_load=-1, bool binary_mode=false) +
Here the inputs and the targets are in separated files. +Input and target frame sizes are therefore auto-detected. +One file must correspond to one sequence. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
IOAscii +
IOBin +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DiskXFile.html b/torch3/manual/DiskXFile.html new file mode 100644 index 0000000..e235505 --- /dev/null +++ b/torch3/manual/DiskXFile.html @@ -0,0 +1,192 @@ + + + + + class DiskXFile + + + + +

class DiskXFile

A file on the disk.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] DiskXFile(const char* file_name, const char* open_flags) +
Open "file_name" with the flags open_flags +
+[more] DiskXFile(FILE* file_) +
Use the given file +
+[more]static bool isLittleEndianProcessor() +
Returns true if the processor uses the little endian coding format +
+[more]static bool isBigEndianProcessor() +
Returns true if the processor uses the big endian coding format +
+[more]static bool isNativeMode() +
Returns true if we'll load/save using the native mode +
+[more]static void setNativeMode() +
We'll load/save using native mode. +
+[more]static void setLittleEndianMode() +
We'll load/save using little endian mode. +
+[more]static void setBigEndianMode() +
We'll load/save using big endian mode. +

+ +
+

Inherited from XFile:

+
+

+

Public Methods

+ovirtual int read(void* ptr, int block_size, int n_blocks) +
+ovirtual int write(void* ptr, int block_size, int n_blocks) +
+oint taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
+oint taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
+ovirtual int eof() +
+ovirtual int flush() +
+ovirtual int seek(long offset, int whence) +
+ovirtual long tell() +
+ovirtual void rewind() +
+ovirtual int printf(const char* format, ...) +
+ovirtual int scanf(const char* format, void* ptr) +
+ovirtual char* gets(char* dest, int size_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A file on the disk. + +

+
+ + + +
o DiskXFile(const char* file_name, const char* open_flags) +
Open "file_name" with the flags open_flags +

+ + +

o DiskXFile(FILE* file_) +
Use the given file +

+ + +

ostatic bool isLittleEndianProcessor() +
Returns true if the processor uses the little endian coding format +

+ + +

ostatic bool isBigEndianProcessor() +
Returns true if the processor uses the big endian coding format +

+ + +

ostatic bool isNativeMode() +
Returns true if we'll load/save using the native mode +

+ + +

ostatic void setNativeMode() +
We'll load/save using native mode. +We use little endian iff the computer uses little endian. +We use big endian iff the computer uses big endian. +

+ + +

ostatic void setLittleEndianMode() +
We'll load/save using little endian mode. +It means that if the computer doesn't use Little Endian, +data will be converted. +

+ + +

ostatic void setBigEndianMode() +
We'll load/save using big endian mode. +It means that if the computer doesn't use Big Endian, +data will be converted. +

+
+
Direct child classes: +
PipeXFile
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Distribution.html b/torch3/manual/Distribution.html new file mode 100644 index 0000000..f856228 --- /dev/null +++ b/torch3/manual/Distribution.html @@ -0,0 +1,344 @@ + + + + + class Distribution + + + + +

class Distribution

This class is designed to handle generative distribution models such as Gaussian Mixture Models and Hidden Markov Models.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real log_probability +
the log likelihood +
+[more]Sequence* log_probabilities +
the log likelihood for each frame when available +

+ +

+

Public Methods

+[more] Distribution(int n_inputs_, int n_params_=0) +
+[more]virtual real logProbability(Sequence* inputs) +
Returns the log probability of a sequence represented by inputs +
+[more]virtual real viterbiLogProbability(Sequence* inputs) +
Returns the viterbi score of a sequence represented by inputs +
+[more]virtual real frameLogProbability(int t, real* f_inputs) +
Returns the log probability of a frame of a sequence +
+[more]virtual real viterbiFrameLogProbability(int t, real* f_inputs) +
Returns the log probability of a frame of a sequence on viterbi mode +
+[more]virtual void eMIterInitialize() +
Methods used to initialize the model at the beginning of each EM iteration +
+[more]virtual void iterInitialize() +
Methods used to initialize the model at the beginning of each gradient descent iteration +
+[more]virtual void eMSequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each example during EM training +
+[more]virtual void sequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each example during gradient descent training +
+[more]virtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
The backward step of EM for a sequence +
+[more]virtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
The backward step of EM for a frame +
+[more]virtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
The backward step of Viterbi learning for a sequence +
+[more]virtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
The backward step of Viterbi for a frame +
+[more]virtual void eMUpdate() +
The update after each iteration for EM +
+[more]virtual void update() +
The update after each gradient iteration +
+[more]virtual void decode(Sequence* inputs) +
For some distribution like SpeechHMM, decodes the most likely path +
+[more]virtual void eMForward(Sequence* inputs) +
Same as forward, but for EM +
+[more]virtual void viterbiForward(Sequence* inputs) +
Same as forward, but for Viterbi +
+[more]virtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Same as backward, but for one frame only +
+[more]virtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
Same as backward, but for Viterbi +
+[more]virtual void frameDecision(int t, real* decision) +
Returns the decision of a frame of a sequence +

+ +

+

Public Members

+[more] Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class is designed to handle generative distribution models +such as Gaussian Mixture Models and Hidden Markov Models. As +distribution inherits from GradientMachine, they can be trained +by gradient descent or by Expectation Maximization (EM) or even +Viterbi. + +

Note that the output of a distribution is the negative log likelihood. + +

+
+ + + +
oreal log_probability +
the log likelihood +

+ + +

oSequence* log_probabilities +
the log likelihood for each frame when available +

+ + +

o Distribution(int n_inputs_, int n_params_=0) +

+ + +

ovirtual real logProbability(Sequence* inputs) +
Returns the log probability of a sequence represented by inputs +

+ + +

ovirtual real viterbiLogProbability(Sequence* inputs) +
Returns the viterbi score of a sequence represented by inputs +

+ + +

ovirtual real frameLogProbability(int t, real* f_inputs) +
Returns the log probability of a frame of a sequence +

+ + +

ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
Returns the log probability of a frame of a sequence on viterbi mode +

+ + +

ovirtual void eMIterInitialize() +
Methods used to initialize the model at the beginning of each +EM iteration +

+ + +

ovirtual void iterInitialize() +
Methods used to initialize the model at the beginning of each +gradient descent iteration +

+ + +

ovirtual void eMSequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each +example during EM training +

+ + +

ovirtual void sequenceInitialize(Sequence* inputs) +
Methods used to initialize the model at the beginning of each +example during gradient descent training +

+ + +

ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
The backward step of EM for a sequence +

+ + +

ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
The backward step of EM for a frame +

+ + +

ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
The backward step of Viterbi learning for a sequence +

+ + +

ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
The backward step of Viterbi for a frame +

+ + +

ovirtual void eMUpdate() +
The update after each iteration for EM +

+ + +

ovirtual void update() +
The update after each gradient iteration +

+ + +

ovirtual void decode(Sequence* inputs) +
For some distribution like SpeechHMM, decodes the most likely path +

+ + +

ovirtual void eMForward(Sequence* inputs) +
Same as forward, but for EM +

+ + +

ovirtual void viterbiForward(Sequence* inputs) +
Same as forward, but for Viterbi +

+ + +

ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Same as backward, but for one frame only +

+ + +

ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
Same as backward, but for Viterbi +

+ + +

o Returns the decision of the distribution +
Returns the decision of the distribution +

+ + +

ovirtual void frameDecision(int t, real* decision) +
Returns the decision of a frame of a sequence +

+
+
Direct child classes: +
TableLookupDistribution
+SpeechMLPDistr
+ParzenDistribution
+Multinomial
+HMM
+DiagonalGMM
+
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/DotKernel.html b/torch3/manual/DotKernel.html new file mode 100644 index 0000000..82ffdd5 --- /dev/null +++ b/torch3/manual/DotKernel.html @@ -0,0 +1,105 @@ + + + + + class DotKernel + + + + +

class DotKernel

DotProduct Kernel.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] DotKernel(real s_=1.) +

+ +
+

Inherited from Kernel:

+
+

+

Public Methods

+ovirtual real eval(Sequence* x, Sequence* y) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
DotProduct Kernel. +k(x,y) = s*(x.y). + +

+
+ + + +
o DotKernel(real s_=1.) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/EMTrainer.html b/torch3/manual/EMTrainer.html new file mode 100644 index 0000000..6ebf0b5 --- /dev/null +++ b/torch3/manual/EMTrainer.html @@ -0,0 +1,153 @@ + + + + + class EMTrainer + + + + +

class EMTrainer

This class is used to train any distribution using the EM algorithm.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Distribution* distribution +
the distribution to train +
+[more]real end_accuracy +
the stopping criterion regarding the accuracy for EM +
+[more]int max_iter +
the stopping criterion regarding the number of iterations for EM +
+[more]bool viterbi +
when viterbi is true, use Viterbi training instead of EM training +

+ +

+

Public Methods

+[more] EMTrainer(Distribution* distribution_) +
+[more]virtual void decode(MeasurerList* measurers) +
this method computes the most likely path into the distribution. +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class is used to train any distribution using the EM algorithm. +It can also train using the Viterbi training algorithm. + +

+
+ + + +
oDistribution* distribution +
the distribution to train +

+ + +

oreal end_accuracy +
the stopping criterion regarding the accuracy for EM +

+ + +

oint max_iter +
the stopping criterion regarding the number of iterations for EM +

+ + +

obool viterbi +
when viterbi is true, use Viterbi training instead of EM training +

+ + +

o EMTrainer(Distribution* distribution_) +

+ + +

ovirtual void decode(MeasurerList* measurers) +
this method computes the most likely path into the distribution. +mainly used for sequential distribution such as HMMs. +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/EditDistance.html b/torch3/manual/EditDistance.html new file mode 100644 index 0000000..9cda3e4 --- /dev/null +++ b/torch3/manual/EditDistance.html @@ -0,0 +1,271 @@ + + + + + class EditDistance + + + + +

class EditDistance

This class can be used to compute the "edit distance" between two sequences.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real accuracy +
the total edit distance between two sequences +
+[more]int n_insert +
the number of insertions (weighted by their cost) +
+[more]int n_delete +
the number of deletions (weighted by their cost) +
+[more]int n_subst +
the number of substitutions (weighted by their cost) +
+[more]int n_seq +
the number of sequences measured (used to normalize dist by n_seq) +
+[more]int insert_cost +
the cost of one insertion +
+[more]int delete_cost +
the cost of one deletion +
+[more]int subst_cost +
the cost of one substitution +
+[more]int* obtained +
the obtained sequence +
+[more]int obt_size +
the size of the obtained sequence +
+[more]int* desired +
the desired sequence +
+[more]int des_size +
the size of the desired sequence +
+[more]int** confusion +
the confusion matrix itself +
+[more]int n_confusion +
the number of symbols +
+[more]int* conf_ins +
insertions and deletions +
+[more]bool is_confusion +
do we want a confusion matrix? +

+ +

+

Public Methods

+[more] EditDistance(bool is_confusion_=false) +
+[more]virtual void setCosts(int i_cost, int d_cost, int s_cost) +
sets the different costs +
+[more]virtual void distance(int* obtained, int obt_size, int* desired, int des_size) +
computes the edit distance between obtained and desired +
+[more]virtual void add(EditDistance* d) +
accumulates the distances of the current object and the given object +
+[more]virtual void print(XFile* f) +
prints the edit distance and optionally the sequences +
+[more]virtual void printRatio(XFile* f) +
prints the edit distance ratio (divided by the number of sequnces) and optionally the obtained and desired sequences +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to compute the "edit distance" between +two sequences. It computes the number of insertions, deletions and +substitutions. The overall distance is the sum of these numbers +weighted by their cost (which are intergers equal to 1 by default). + +

+
+ + + +
oreal accuracy +
the total edit distance between two sequences +

+ + +

oint n_insert +
the number of insertions (weighted by their cost) +

+ + +

oint n_delete +
the number of deletions (weighted by their cost) +

+ + +

oint n_subst +
the number of substitutions (weighted by their cost) +

+ + +

oint n_seq +
the number of sequences measured (used to normalize dist by n_seq) +

+ + +

oint insert_cost +
the cost of one insertion +

+ + +

oint delete_cost +
the cost of one deletion +

+ + +

oint subst_cost +
the cost of one substitution +

+ + +

oint* obtained +
the obtained sequence +

+ + +

oint obt_size +
the size of the obtained sequence +

+ + +

oint* desired +
the desired sequence +

+ + +

oint des_size +
the size of the desired sequence +

+ + +

oint** confusion +
the confusion matrix itself +

+ + +

oint n_confusion +
the number of symbols +

+ + +

oint* conf_ins +
insertions and deletions +

+ + +

obool is_confusion +
do we want a confusion matrix? +

+ + +

o EditDistance(bool is_confusion_=false) +

+ + +

ovirtual void setCosts(int i_cost, int d_cost, int s_cost) +
sets the different costs +

+ + +

ovirtual void distance(int* obtained, int obt_size, int* desired, int des_size) +
computes the edit distance between obtained and desired +

+ + +

ovirtual void add(EditDistance* d) +
accumulates the distances of the current object and the given object +

+ + +

ovirtual void print(XFile* f) +
prints the edit distance and optionally the sequences +

+ + +

ovirtual void printRatio(XFile* f) +
prints the edit distance ratio (divided by the number of sequnces) +and optionally the obtained and desired sequences +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/EditDistanceMeasurer.html b/torch3/manual/EditDistanceMeasurer.html new file mode 100644 index 0000000..c4ceda1 --- /dev/null +++ b/torch3/manual/EditDistanceMeasurer.html @@ -0,0 +1,147 @@ + + + + + class EditDistanceMeasurer + + + + +

class EditDistanceMeasurer

This class can be used to measure and print an EditDistance object.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]EditDistance* edit +
the EditDistance to measure +
+[more]EditDistance* sum +
an accumulator of EditDistance objects, to compute statistics +
+[more]bool print_ex +
do we print the edit distance for each example? +

+ +

+

Public Methods

+[more] EditDistanceMeasurer(EditDistance* edit_, DataSet* data_, XFile* file_, bool is_confusion_=false) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to measure and print an EditDistance object. +It is used for instance in speech recognition experiments. + +

+
+ + + +
oEditDistance* edit +
the EditDistance to measure +

+ + +

oEditDistance* sum +
an accumulator of EditDistance objects, to compute statistics +

+ + +

obool print_ex +
do we print the edit distance for each example? +

+ + +

o EditDistanceMeasurer(EditDistance* edit_, DataSet* data_, XFile* file_, bool is_confusion_=false) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ExampleFrameSelectorDataSet.html b/torch3/manual/ExampleFrameSelectorDataSet.html new file mode 100644 index 0000000..731b9ce --- /dev/null +++ b/torch3/manual/ExampleFrameSelectorDataSet.html @@ -0,0 +1,145 @@ + + + + + class ExampleFrameSelectorDataSet + + + + +

class ExampleFrameSelectorDataSet

This dataset is empty at the begining.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] ExampleFrameSelectorDataSet(DataSet* data_) +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid init(int n_examples_, int n_inputs_, int n_targets_) +
+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
+This dataset is empty at the begining. Each subsequence of the original dataset +can be added/remove by the methods: +
    +
  • addExample +
  • removeExample +
+
+
+ + + +
o ExampleFrameSelectorDataSet(DataSet* data_) +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +
See Also:
FrameSelectorDataSet +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Exp.html b/torch3/manual/Exp.html new file mode 100644 index 0000000..1545b9c --- /dev/null +++ b/torch3/manual/Exp.html @@ -0,0 +1,148 @@ + + + + + class Exp + + + + +

class Exp

Exponentiel layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Exp(int n_units) +
Create a layer of size n_units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Exponentiel layer for GradientMachine. + +

The number of inputs/outputs is the number +of units for this machine. +Formally speaking, . + +

+
+ + + +
o Exp(int n_units) +
Create a layer of size n_units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/FileListCmdOption.html b/torch3/manual/FileListCmdOption.html new file mode 100644 index 0000000..4be134c --- /dev/null +++ b/torch3/manual/FileListCmdOption.html @@ -0,0 +1,154 @@ + + + + + class FileListCmdOption + + + + +

class FileListCmdOption

This class take a file name in the command line, and reads a list of files contained in this file.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]char** file_names +
Contains the file names after reading the command line +
+[more]int n_files +
Number of files that have been read +

+ +

+

Public Methods

+[more] FileListCmdOption(const char* name_, const char* help_="", bool save_=false) +

+ +
+

Inherited from CmdOption:

+
+

+

Public Fields

+ochar* name +
+ochar* type_name +
+ochar* help +
+obool save +
+obool is_setted +

+ +

+

Public Methods

+ovirtual void initValue() +
+ovirtual void printValue(XFile* file_) +
+ovirtual void read(int* argc_, char*** argv_) +
+obool isOption(bool set_=false) +
+obool isArgument(bool set_=false) +
+obool isText(bool set_=false) +
+obool isMasterSwitch(bool set_=false) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class take a file name in the command line, +and reads a list of files contained in this +file. + +

In fact, there is a special case: it checks first +if "-one_file" the current argument on the command +line. If true, then it reads the next argument which +will be the only file in the list. + +

+
+ + + +
ochar** file_names +
Contains the file names after reading the command line +

+ + +

oint n_files +
Number of files that have been read +

+ + +

o FileListCmdOption(const char* name_, const char* help_="", bool save_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/FrameSeg.html b/torch3/manual/FrameSeg.html new file mode 100644 index 0000000..5ea4437 --- /dev/null +++ b/torch3/manual/FrameSeg.html @@ -0,0 +1,132 @@ + + + + + class FrameSeg + + + + +

class FrameSeg

This class keeps track of all information to compute errors at the frame level
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]LexiconInfo* lexicon +
the corresponding lexicon +
+[more]Sequence* target +
the target sequence +
+[more]Sequence* obtained +
the obtained sequence +
+[more]int* states_to_model_states +
the translation between words, states, model_states +

+ +

+

Public Methods

+[more] FrameSeg(LexiconInfo* lexicon_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class keeps track of all information to compute errors at the +frame level + +

+
+ + + +
oLexiconInfo* lexicon +
the corresponding lexicon +

+ + +

oSequence* target +
the target sequence +

+ + +

oSequence* obtained +
the obtained sequence +

+ + +

oint* states_to_model_states +
the translation between words, states, model_states +

+ + +

o FrameSeg(LexiconInfo* lexicon_) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/FrameSegMeasurer.html b/torch3/manual/FrameSegMeasurer.html new file mode 100644 index 0000000..a63f09a --- /dev/null +++ b/torch3/manual/FrameSegMeasurer.html @@ -0,0 +1,148 @@ + + + + + class FrameSegMeasurer + + + + +

class FrameSegMeasurer

This class can be used to save the frame segmentation of a SimpleDecoderSpeechHMM in a file.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]FrameSeg* frameseg +
the pointer to the corresponding frameseg object +
+[more]int n_per_frame +
when timing is required, what is the number of tics per frames +
+[more]int n_correct +
some stats +

+ +

+

Public Methods

+[more] FrameSegMeasurer(FrameSeg* frameseg_, DataSet* data_, XFile* file_, char** file_list_=NULL, int n_file_list_ = 0) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to save the frame segmentation of a +SimpleDecoderSpeechHMM +in a file. Optionally, it also prints the corresponding target segmentation. + +

+
+ + + +
oFrameSeg* frameseg +
the pointer to the corresponding frameseg object +

+ + +

oint n_per_frame +
when timing is required, what is the number of tics per frames +

+ + +

oint n_correct +
some stats +

+ + +

o FrameSegMeasurer(FrameSeg* frameseg_, DataSet* data_, XFile* file_, char** file_list_=NULL, int n_file_list_ = 0) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/FrameSelectorDataSet.html b/torch3/manual/FrameSelectorDataSet.html new file mode 100644 index 0000000..3b6f061 --- /dev/null +++ b/torch3/manual/FrameSelectorDataSet.html @@ -0,0 +1,224 @@ + + + + + class FrameSelectorDataSet + + + + +

class FrameSelectorDataSet

A dataset used to select some frames of another dataset.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]DataSet* data +
DataSet where we will select frames +
+[more]int* n_selected_input_frames +
Number of input selected frames, for each example +
+[more]int* n_selected_target_frames +
Number of target selected frames, for each example +
+[more]int** input_frames_indices +
Indices of input selected frames, for each example +
+[more]int** target_frames_indices +
Indices of target selected frames, for each example +

+ +

+

Public Methods

+[more] FrameSelectorDataSet(DataSet* data_) +
+[more]void selectInputFrames(int t_, int* frames_indices_, int n_frames_) +
Select input frames of the example t. +
+[more]void selectTargetFrames(int t_, int* frames_indices_, int n_frames_) +
Same as selectInputFrames(), but for targets +
+[more]void unselectInputFrames(int t_) +
Unselect inputs frames of the example t. +
+[more]void unselectTargetFrames(int t_) +
Unselect targets frames of the example t. +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid init(int n_examples_, int n_inputs_, int n_targets_) +
+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A dataset used to select some frames of another dataset. +It takes a dataset in the constructor. Then you call +select functions to select frames. After that, when +you will do a setExample() the example of the previous +dataset will be returned in inputs and targets fields, +with the right frames... + +

+
+ + + +
oDataSet* data +
DataSet where we will select frames +

+ + +

oint* n_selected_input_frames +
Number of input selected frames, for each example +

+ + +

oint* n_selected_target_frames +
Number of target selected frames, for each example +

+ + +

oint** input_frames_indices +
Indices of input selected frames, for each example +

+ + +

oint** target_frames_indices +
Indices of target selected frames, for each example +

+ + +

o FrameSelectorDataSet(DataSet* data_) +

+ + +

ovoid selectInputFrames(int t_, int* frames_indices_, int n_frames_) +
Select input frames of the example t. +Frames indices are given by frames_indices_. +The size of frames_indices_ is given by n_frames_. +Takes in account pushed subsets. +

+ + +

ovoid selectTargetFrames(int t_, int* frames_indices_, int n_frames_) +
Same as selectInputFrames(), but for targets +

+ + +

ovoid unselectInputFrames(int t_) +
Unselect inputs frames of the example t. +Takes in account pushed subsets. +

+ + +

ovoid unselectTargetFrames(int t_) +
Unselect targets frames of the example t. +Takes in account pushed subsets. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/GaussianKernel.html b/torch3/manual/GaussianKernel.html new file mode 100644 index 0000000..c6208ea --- /dev/null +++ b/torch3/manual/GaussianKernel.html @@ -0,0 +1,104 @@ + + + + + class GaussianKernel + + + + +

class GaussianKernel

Gaussian Kernel
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] GaussianKernel(real g_) +

+ +
+

Inherited from Kernel:

+
+

+

Public Methods

+ovirtual real eval(Sequence* x, Sequence* y) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Gaussian Kernel + +

+
+ + + +
o GaussianKernel(real g_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/General.html b/torch3/manual/General.html new file mode 100644 index 0000000..d5d1531 --- /dev/null +++ b/torch3/manual/General.html @@ -0,0 +1,16 @@ + + + + + General Bits + + + + +
+
+

Alphabetic index Hierarchy of classes


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Givensmatrixoperationsroutines..html b/torch3/manual/Givensmatrixoperationsroutines..html new file mode 100644 index 0000000..a56bff4 --- /dev/null +++ b/torch3/manual/Givensmatrixoperationsroutines..html @@ -0,0 +1,50 @@ + + + + + Givens matrix operations routines. + + + + +

Givens matrix operations routines.

+
+

+
+void mx_givens(real x, real y, real* c, real* s) +
Returns c, s parameters for Givens rotation to eliminate y in the vector [ x y ]' +
+void mx_rot_vec(Vec* x, int i, int k, real c, real s, Vec* out) +
Apply Givens rotation to x's i and k components +
+void mx_rot_rows(Mat* mat, int i, int k, real c, real s, Mat* out) +
Premultiply mat by givens rotation described by c,s +
+void mx_rot_cols(Mat* mat, int i, int k, real c, real s, Mat* out) +
Postmultiply mat by givens rotation described by c,s +

+ + + +
+

Documentation

+
+Givens matrix operations routines. +Routines for calculating and applying Givens rotations for/to +vectors and also to matrices by row and by column. + +

Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/GradientMachine.html b/torch3/manual/GradientMachine.html new file mode 100644 index 0000000..08360f3 --- /dev/null +++ b/torch3/manual/GradientMachine.html @@ -0,0 +1,271 @@ + + + + + class GradientMachine + + + + +

class GradientMachine

Gradient machine: machine which can be trained with a gradient descent.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_inputs +
Frame size of inputs sequences +
+[more]int n_outputs +
Frame size of outputs sequences +
+[more]Parameters* params +
Contains all parameters which will be updated with the gradient descent. +
+[more]Parameters* der_params +
Contains the derivatives for all parameters. +
+[more]Sequence* beta +
Contains the derivative with respect to the inputs +

+ +

+

Public Methods

+[more] GradientMachine(int n_inputs_, int n_outputs_, int n_params_=0) +
Initialize a gradient machine with n_inputs_ for the input frame size, n_outputs_ for the output frame size and n_params_ parameters. +
+[more]virtual void iterInitialize() +
This function is called before each training iteration. +
+[more]virtual void forward(Sequence* inputs) +
Given a sequence, update outputs. +
+[more]virtual void backward(Sequence* inputs, Sequence* alpha) +
Given a sequence, update the derivative with respect to the input (beta) and der_params. +
+[more]virtual void setPartialBackprop(bool flag=true) +
Set the partial backprop flag +
+[more]virtual void frameForward(int t, real* f_inputs, real* f_outputs) +
Given a frame f_inputs, updates f_outputs. +
+[more]virtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Given the f_inputs and the derivatives alpha_ with respect to the outputs, updates the derivative with respect to the inputs (beta_) and der_params. +
+[more]virtual void loadXFile(XFile* file) +
By default, load the params field +
+[more]virtual void saveXFile(XFile* file) +
By default, save the params field +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Gradient machine: machine which can +be trained with a gradient descent. + +

Gradient machines take in inputs sequences which have always the same +frame size, given by n_inputs, and outputs sequences which have always +the same frame size too, given by n_outputs. + +

+
+ + + +
oint n_inputs +
Frame size of inputs sequences +

+ + +

oint n_outputs +
Frame size of outputs sequences +

+ + +

oParameters* params +
Contains all parameters which will be +updated with the gradient descent. +Almost all machines will have only one +node in params. +

+ + +

oParameters* der_params +
Contains the derivatives for all parameters. +Warning: params and der_params +must have the same structure. +

+ + +

oSequence* beta +
Contains the derivative with respect to the inputs +

+ + +

o GradientMachine(int n_inputs_, int n_outputs_, int n_params_=0) +
Initialize a gradient machine with n_inputs_ for the input frame size, +n_outputs_ for the output frame size and n_params_ parameters. +If n_inputs_ is 0, no beta sequence will be allocated. +If n_outputs_ is 0, no outputs sequence will be allocated. +

+ + +

ovirtual void iterInitialize() +
This function is called before each +training iteration. +By default, do nothing. +

+ + +

ovirtual void forward(Sequence* inputs) +
Given a sequence, update outputs. +By default, it uses frameForward(), to update each output frame +given each input frame. It supposes by default the number of input +and output frames is the same. +

+ + +

ovirtual void backward(Sequence* inputs, Sequence* alpha) +
Given a sequence, update the derivative with respect to the input (beta) +and der_params. If partial_backprop is false, don't update beta. +By default, it uses frameBackward(), to update each beta frame +given each input and alpha frame. It supposes by default the number of input +and output frames is the same. +

+ + +

ovirtual void setPartialBackprop(bool flag=true) +
Set the partial backprop flag +

+ + +

ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
Given a frame f_inputs, updates f_outputs. Used to easily create new classes. +It is called by the default forward(), and it does nothing by default. +If your machine needs to do special things on sequence (if input sequence do not +have the same size as the output sequence), don't overload this function, but +overload forward(). t is the current frame to be forwarded. +

+ + +

ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
Given the f_inputs and the derivatives alpha_ with +respect to the outputs, updates the derivative with respect to the inputs (beta_) +and der_params. +It is called by the default backward(), and it does nothing by default. +If your machine needs to do special things on sequence (if input sequence do not +have the same size as the output sequence), don't overload this function, but +overload backward(). t is the current frame to be back-propagated. +

+ + +

ovirtual void loadXFile(XFile* file) +
By default, load the params field +

+ + +

ovirtual void saveXFile(XFile* file) +
By default, save the params field +

+
+
Direct child classes: +
TemporalSubSampling
+TemporalMean
+TemporalConvolution
+Tanh
+SumMachine
+SpatialSubSampling
+SpatialConvolution
+SoftPlus
+SoftMax
+Sigmoid
+Mixer
+LogSoftMax
+LogSigmoid
+LogRBF
+LogMixer
+Linear
+InputsSelect
+Exp
+Distribution
+Criterion
+ConnectedMachine
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
StochasticGradient +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Grammar.html b/torch3/manual/Grammar.html new file mode 100644 index 0000000..9596137 --- /dev/null +++ b/torch3/manual/Grammar.html @@ -0,0 +1,139 @@ + + + + + class Grammar + + + + +

class Grammar

This class contains the grammar of accepted sentences for a speech recognition experiment such as the one using SimpleDecoderSpeechHMM A grammar is a transition table where each node is a word.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_words +
the number of words in the grammar (different than the number of words in the lexicon, because the same word can appear twice in the grammar) +
+[more]int* words +
the index of the words (in the lexicon object) +
+[more]int* start +
this vector is used in SimpleDecoderSpeechHMM to keep the state index in the decoding state matrix, corresponding to the given word +
+[more]bool** transitions +
the transition matrix. +

+ +

+

Public Methods

+[more] Grammar(int n_words_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class contains the grammar of accepted sentences for a +speech recognition experiment such as the one using SimpleDecoderSpeechHMM +A grammar is a transition table where each node is a word. +The user is responsible to set the transition table as he wishes. +(by default, there are no transition!) + +

+
+ + + +
oint n_words +
the number of words in the grammar (different than the number +of words in the lexicon, because the same word can appear twice +in the grammar) +

+ + +

oint* words +
the index of the words (in the lexicon object) +

+ + +

oint* start +
this vector is used in SimpleDecoderSpeechHMM to keep the state +index in the decoding state matrix, corresponding to the given word +

+ + +

obool** transitions +
the transition matrix. each true transition (i,j) means the +word whose index is i can be followed by the word whose index is j +

+ + +

o Grammar(int n_words_) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/HIER.html b/torch3/manual/HIER.html new file mode 100644 index 0000000..2936e11 --- /dev/null +++ b/torch3/manual/HIER.html @@ -0,0 +1,213 @@ + + +
Torch Reference Manual +
[Torch] +
http://www.torch.ch +
+

Hierarchy of Classes

+ +
Torch. +The Ultimate Machine Learning Library.
+
+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/HIERjava.html b/torch3/manual/HIERjava.html new file mode 100644 index 0000000..0c19bf0 --- /dev/null +++ b/torch3/manual/HIERjava.html @@ -0,0 +1,133 @@ + + +
Torch Reference Manual +
[Torch] +
http://www.torch.ch +
+

Hierarchy of classes

+
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ alphabetic index


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/HMM.html b/torch3/manual/HMM.html new file mode 100644 index 0000000..6677b11 --- /dev/null +++ b/torch3/manual/HMM.html @@ -0,0 +1,374 @@ + + + + + class HMM + + + + +

class HMM

This class implements a Hidden Markov Model distribution.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_states +
The number of states of the HMM. +
+[more]real prior_transitions +
a prior on the transition probabilities +
+[more]Distribution** states +
keep the emission distributions +
+[more]Distribution** shared_states +
if the states are in fact shared in some way or another, the original ones are in shared_states +
+[more]real** transitions +
the initial transitions between states are kept as a matrix +
+[more]real** log_transitions +
in fact, we keep the transitions in log +
+[more]real** dlog_transitions +
the derivative of the log transitions for gradient descent +
+[more]real** transitions_acc +
the accumulators of the transitions for EM +
+[more]Sequence* log_alpha +
accumulator used in the forward phase to compute log likelihood +
+[more]Sequence* log_beta +
accumulator used in the backward phase to compute log likelihood +
+[more]Sequence* arg_viterbi +
for each state, for each time step, keep the best predecessor +
+[more]int last_arg_viterbi +
arg_viterbi of the finishing state +
+[more]Sequence* viterbi_sequence +
for each time step, keep the best state +
+[more]Sequence* log_probabilities_s +
keep for each time step and each model its emission log probability +
+[more]bool initialize +
do we need to initialize the model? +

+ +

+

Public Methods

+[more]virtual void printTransitions(bool real_values=false, bool transitions_only=false) +
this method can be used for debugging purpose to see the transitions +
+[more]virtual void logAlpha(Sequence* inputs) +
computes the log_alpha during forward phase of EM +
+[more]virtual void logBeta(Sequence* inputs) +
computes the log_beta during backward phase of EM +
+[more]virtual void logViterbi(Sequence* inputs) +
computes the log_viterbi during forward phase of Viterbi +
+[more]virtual void decode(Sequence* input) +
this method returns the state sequence associated to the input +
+[more]virtual void logProbabilities(Sequence* inputs) +
computes for each state and each time step of the sequence inputs its associated emission probability +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class implements a Hidden Markov Model distribution. It can be trained +either by EM, Viterbi, or Gradient Descent. + +

Note that this kind of HMM always contain one initial state and +one final state. Both are non-emitting. + +

Note that the log_probabilities is the average over all frames of the +log_probability of the example. + +

+
+ + + +
oint n_states +
The number of states of the HMM. +the first model is the initial state, +the last model is the final (absorbing) state, +(neither of them are emitting). +hence, n_states > 2 +

+ + +

oreal prior_transitions +
a prior on the transition probabilities +

+ + +

oDistribution** states +
keep the emission distributions +

+ + +

oDistribution** shared_states +
if the states are in fact shared in some way or another, the original ones are in shared_states +

+ + +

oreal** transitions +
the initial transitions between states are kept as a matrix +

+ + +

oreal** log_transitions +
in fact, we keep the transitions in log +

+ + +

oreal** dlog_transitions +
the derivative of the log transitions for gradient descent +

+ + +

oreal** transitions_acc +
the accumulators of the transitions for EM +

+ + +

oSequence* log_alpha +
accumulator used in the forward phase to compute log likelihood +

+ + +

oSequence* log_beta +
accumulator used in the backward phase to compute log likelihood +

+ + +

oSequence* arg_viterbi +
for each state, for each time step, keep the best predecessor +

+ + +

oint last_arg_viterbi +
arg_viterbi of the finishing state +

+ + +

oSequence* viterbi_sequence +
for each time step, keep the best state +

+ + +

oSequence* log_probabilities_s +
keep for each time step and each model its emission log probability +

+ + +

obool initialize +
do we need to initialize the model? +

+ + +

ovirtual void printTransitions(bool real_values=false, bool transitions_only=false) +
this method can be used for debugging purpose to see the transitions +

+ + +

ovirtual void logAlpha(Sequence* inputs) +
computes the log_alpha during forward phase of EM +

+ + +

ovirtual void logBeta(Sequence* inputs) +
computes the log_beta during backward phase of EM +

+ + +

ovirtual void logViterbi(Sequence* inputs) +
computes the log_viterbi during forward phase of Viterbi +

+ + +

ovirtual void decode(Sequence* input) +
this method returns the state sequence associated to the input +

+ + +

ovirtual void logProbabilities(Sequence* inputs) +
computes for each state and each time step of the sequence inputs +its associated emission probability +

+
+
Direct child classes: +
SpeechHMM
+MAPHMM
+
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/HTKDataSet.html b/torch3/manual/HTKDataSet.html new file mode 100644 index 0000000..4a24935 --- /dev/null +++ b/torch3/manual/HTKDataSet.html @@ -0,0 +1,165 @@ + + + + + class HTKDataSet + + + + +

class HTKDataSet

This dataset can deal with the HTK format for features and targets.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] HTKDataSet(const char* inputs_filenames, bool one_file_is_one_sequence, int max_load, const char* targets_filename = NULL, LexiconInfo* lex_=NULL, bool words=true) +
+[more] HTKDataSet(char** inputs_filenames, char** targets_filename, int n_files_, bool one_file_is_one_sequence, int max_load, LexiconInfo* lex_=NULL, bool words=true) +

+ +
+

Inherited from MemoryDataSet:

+
+

+

Public Fields

+oSequence** inputs_array +
+oSequence** targets_array +

+ +

+

Public Methods

+ovoid init(IOSequence* io_inputs, IOSequence* io_outputs) +
+ovoid setInputs(Sequence** inputs_, int n_sequences_) +
+ovoid setTargets(Sequence** targets_, int n_sequences_) +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This dataset can deal with the HTK format for features and targets. + +

+
+ + + +
o HTKDataSet(const char* inputs_filenames, bool one_file_is_one_sequence, int max_load, const char* targets_filename = NULL, LexiconInfo* lex_=NULL, bool words=true) +

+ + +

o HTKDataSet(char** inputs_filenames, char** targets_filename, int n_files_, bool one_file_is_one_sequence, int max_load, LexiconInfo* lex_=NULL, bool words=true) +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +
See Also:
MatDataSet +
IOHTK +
IOHTKTarget +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Householdertransformationroutines..html b/torch3/manual/Householdertransformationroutines..html new file mode 100644 index 0000000..9a81826 --- /dev/null +++ b/torch3/manual/Householdertransformationroutines..html @@ -0,0 +1,47 @@ + + + + + Householder transformation routines. + + + + +

Householder transformation routines.

+
+

+
+void mxHhVec(Vec* vec, int i0, real* beta, Vec* out, real* newval) +
Calulates Householder vector. +
+void mxHhTrVec(Vec* hh, real beta, int i0, Vec* in, Vec* out) +
Apply Householder transformation to vector. +
+void mxHhTrRows(Mat* mat, int i0, int j0, Vec* hh, real beta) +
Transform a matrix by a Householder vector by rows. +

+ + + +
+

Documentation

+
+Householder transformation routines. +Contains routines for calculating householder transformations, +applying them to vectors and matrices by both row and column. + +

Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOAscii.html b/torch3/manual/IOAscii.html new file mode 100644 index 0000000..9408bf8 --- /dev/null +++ b/torch3/manual/IOAscii.html @@ -0,0 +1,141 @@ + + + + + class IOAscii + + + + +

class IOAscii

Handles the standard Ascii sequence format in Torch.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IOAscii(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1) +
Reads the sequence contained in filename. +
+[more]static void saveSequence(XFile* file, Sequence* sequence) +
Saves one sequence in file using the ascii format +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Handles the standard Ascii sequence format in Torch. +The format is the following: +
    +
  • First line should contain the number of frames and the frame size (two int +separated by a space) of the file. +
  • Next lines are frames of the sequence. One frame is one line. (number_of_columns real +at each line, separated by a space). +
+ +

+
+ + + +
o IOAscii(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1) +
Reads the sequence contained in filename. +If one_file_is_one_sequence is false, getSequence() will return one sequence +with one frame at each call. (If calling getSequence(t, foo), +it will put in the sequence foo the frame corresponding to the line t of the file). +Note also that if one_file_is_one_sequence is false, the access to the IO must be +sequential when calling getSequence(). +If max_load_ is positive, it loads only the first max_load_ frames, if one_file_is_one_sequence +is false. +The file will be opened when reading the first sequence, and closed when reading the +last one. +

+ + +

ostatic void saveSequence(XFile* file, Sequence* sequence) +
Saves one sequence in file using the ascii format +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOBin.html b/torch3/manual/IOBin.html new file mode 100644 index 0000000..3e5e7db --- /dev/null +++ b/torch3/manual/IOBin.html @@ -0,0 +1,142 @@ + + + + + class IOBin + + + + +

class IOBin

Handles the standard binary sequence format in Torch.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IOBin(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1, bool is_sequential=true) +
Reads the sequence contained in filename. +
+[more]static void saveSequence(XFile* file, Sequence* sequence) +
Saves sequence in file using the binary format +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Handles the standard binary sequence format in Torch. +The format is the following: +
    +
  • Two int at the beginning of the file for the number of frames and the frame size +of the sequence in the file. +
  • After that, the sequence data, frame after frame. (frame_size real per row). +
+ +

+
+ + + +
o IOBin(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1, bool is_sequential=true) +
Reads the sequence contained in filename. +If one_file_is_one_sequence is false, getSequence() will return one sequence +with one frame at each call. (If calling getSequence(t, foo), +it will put in the sequence foo the frame corresponding to the line t of the file). +Note also that if one_file_is_one_sequence is false, the access to the IO must be +sequential when calling getSequence() if is_sequential is true. (Sequential mode +is faster). +If max_load_ is positive, it loads only the first max_load_ frames, +if one_file_is_one_sequence is false. +The file will be opened when reading the first sequence, and closed when reading the +last one if is_sequential is true. Otherwise, the file will be opened and closed +each time you call getSequence(). +

+ + +

ostatic void saveSequence(XFile* file, Sequence* sequence) +
Saves sequence in file using the binary format +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOBufferize.html b/torch3/manual/IOBufferize.html new file mode 100644 index 0000000..2c5f36b --- /dev/null +++ b/torch3/manual/IOBufferize.html @@ -0,0 +1,152 @@ + + + + + class IOBufferize + + + + +

class IOBufferize

This IO bufferizes the asked sequence of a given IO when calling getSequence().
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]IOSequence* io_torch +
IO to be bufferized +
+[more]Sequence* bufferized_sequence +
The bufferized sequence +
+[more]int bufferized_sequence_index +
The bufferized sequence index +

+ +

+

Public Methods

+[more] IOBufferize(IOSequence* io_torch_) +
+[more]void bufferizeSequence(int t) +
Force sequence t to be bufferized +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This IO bufferizes the asked sequence of a given IO when calling getSequence(). +Then, if the next call of getSequence() ask for the same sequence, it will +return it without asking the given IO. + +

+
+ + + +
oIOSequence* io_torch +
IO to be bufferized +

+ + +

oSequence* bufferized_sequence +
The bufferized sequence +

+ + +

oint bufferized_sequence_index +
The bufferized sequence index +

+ + +

o IOBufferize(IOSequence* io_torch_) +

+ + +

ovoid bufferizeSequence(int t) +
Force sequence t to be bufferized +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOHTK.html b/torch3/manual/IOHTK.html new file mode 100644 index 0000000..ca12ec6 --- /dev/null +++ b/torch3/manual/IOHTK.html @@ -0,0 +1,156 @@ + + + + + class IOHTK + + + + +

class IOHTK

Handles the standard binary sequence format in HTK.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]HTKHeader* header +
Contain the htk header informations +

+ +

+

Public Methods

+[more] IOHTK(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1, bool is_sequential_=false) +
Reads the sequence contained in filename. +
+[more]static void saveSequence(XFile* file, Sequence* sequence, HTKHeader* header_) +
Saves sequence in file using the HTK format +
+[more]char* parmKind2Str(ParmKind kind, char* buf) +
HTK source code +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Handles the standard binary sequence format in HTK. + +

+
+ + + +
oHTKHeader* header +
Contain the htk header informations +

+ + +

o IOHTK(const char* filename_, bool one_file_is_one_sequence_=false, int max_load_=-1, bool is_sequential_=false) +
Reads the sequence contained in filename. +If one_file_is_one_sequence is false, getSequence() will return one sequence +with one frame at each call. (If calling getSequence(t, foo), +it will put in the sequence foo the frame corresponding to the line t of the file). +Note also that if one_file_is_one_sequence is false, the access to the IO must be +sequential when calling getSequence() if is_sequential is true. (Sequential mode +is faster). +If max_load_ is positive, it loads only the first max_load_ frames, +if one_file_is_one_sequence is false. +The file will be opened when reading the first sequence, and closed when reading the +last one if is_sequential is true. Otherwise, the file will be opened and closed +each time you call getSequence(). +

+ + +

ostatic void saveSequence(XFile* file, Sequence* sequence, HTKHeader* header_) +
Saves sequence in file using the HTK format +

+ + +

ochar* parmKind2Str(ParmKind kind, char* buf) +
HTK source code +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +
See Also:
IOBin +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOHTKTarget.html b/torch3/manual/IOHTKTarget.html new file mode 100644 index 0000000..217cea5 --- /dev/null +++ b/torch3/manual/IOHTKTarget.html @@ -0,0 +1,122 @@ + + + + + class IOHTKTarget + + + + +

class IOHTKTarget

Handles the standard Ascii HTK targets/labels format in Torch.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Members

+[more] Saves one sequence in file using the ascii format +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Handles the standard Ascii HTK targets/labels format in Torch. +There are two format: +
    +
  • each line is a word/phoneme +separated by a space). +
  • each line consiste in two integer (begin and end of the sequence) and a string containing the label (word/phoneme) +
+
+
+ + + +
o Saves one sequence in file using the ascii format +
Saves one sequence in file using the ascii format +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +
See Also:
IOAscii +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOMulti.html b/torch3/manual/IOMulti.html new file mode 100644 index 0000000..0c3cd40 --- /dev/null +++ b/torch3/manual/IOMulti.html @@ -0,0 +1,119 @@ + + + + + class IOMulti + + + + +

class IOMulti

This IO takes several IOSequence, and will act as if you had concatened all these IOSequence when calling getMatrix().
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IOMulti(IOSequence** io_files_, int n_files_) +
Takes n_files_ pointers to IOSequence, given in io_files_ +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This IO takes several IOSequence, and will +act as if you had concatened all these IOSequence when +calling getMatrix(). + +

+
+ + + +
o IOMulti(IOSequence** io_files_, int n_files_) +
Takes n_files_ pointers to IOSequence, given in io_files_ +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOSequence.html b/torch3/manual/IOSequence.html new file mode 100644 index 0000000..b1b0f5f --- /dev/null +++ b/torch3/manual/IOSequence.html @@ -0,0 +1,149 @@ + + + + + class IOSequence + + + + +

class IOSequence

Class which provides an ensemble of sequences, which have the same frame size, but could have different number of frames.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_sequences +
Number of sequences in the interface +
+[more]int frame_size +
Frame size of each sequence +

+ +

+

Public Methods

+[more] IOSequence() +
+[more]virtual int getNumberOfFrames(int t) = 0 +
Returns the number of frames of the sequence indexed by t +
+[more]virtual void getSequence(int t, Sequence* sequence) = 0 +
Write the sequence t in sequence. +
+[more]virtual int getTotalNumberOfFrames() = 0 +
Returns the total number of frames in the IO +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Class which provides an ensemble of sequences, which have the same +frame size, but could have different number of frames. + +

+
+ + + +
oint n_sequences +
Number of sequences in the interface +

+ + +

oint frame_size +
Frame size of each sequence +

+ + +

o IOSequence() +

+ + +

ovirtual int getNumberOfFrames(int t) = 0 +
Returns the number of frames of the sequence indexed by t +

+ + +

ovirtual void getSequence(int t, Sequence* sequence) = 0 +
Write the sequence t in sequence. +Sequence must have the size returned by getNumberOfFrames(). +

+ + +

ovirtual int getTotalNumberOfFrames() = 0 +
Returns the total number of frames in the IO +

+
+
Direct child classes: +
IOSub
+IOMulti
+IOHTKTarget
+IOHTK
+IOBufferize
+IOBin
+IOAscii
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOSequenceArray.html b/torch3/manual/IOSequenceArray.html new file mode 100644 index 0000000..79a7458 --- /dev/null +++ b/torch3/manual/IOSequenceArray.html @@ -0,0 +1,122 @@ + + + + + class IOSequenceArray + + + + +

class IOSequenceArray

Load and save in an efficiently manner an array of sequences.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IOSequenceArray() +
+[more]virtual void read(XFile* file, Sequence** sequences_array, int n_sequences, Allocator* allocator_=NULL) +
Read an array of sequences in file. +
+[more]virtual void write(XFile* file, Sequence** sequences_array, int n_sequences) +
Write an array of sequences in file. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Load and save in an efficiently manner an array of sequences. +(in an arbitrary binary format). + +

This could be useful for some (rare) classes which needs to save +sequences which could be in another format that the standard +sequence format (if you plan to use them with strange subclasses of +Sequence). + +

+
+ + + +
o IOSequenceArray() +

+ + +

ovirtual void read(XFile* file, Sequence** sequences_array, int n_sequences, Allocator* allocator_=NULL) +
Read an array of sequences in file. n_sequences will be read. +If allocator_ is non-NULL, it will be used to allocate the memory +of the sequences. Else, the memory of the sequences will be destroyed +when destroying the class. sequences_array must have the size n_sequences. +

+ + +

ovirtual void write(XFile* file, Sequence** sequences_array, int n_sequences) +
Write an array of sequences in file. n_sequences will be written. +sequences_array must have the size n_sequences. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IOSub.html b/torch3/manual/IOSub.html new file mode 100644 index 0000000..e8a0581 --- /dev/null +++ b/torch3/manual/IOSub.html @@ -0,0 +1,119 @@ + + + + + class IOSub + + + + +

class IOSub

IOSequence which does a selection of adjacent columns on another IOSequence, when calling getMatrix().
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IOSub(IOBufferize* io_torch_, int offset_, int frame_size_) +
We will select columns indexed by offset_offset_+frame_size_-1 of the frames provided by io_torch_, when calling getSequence() +

+ +
+

Inherited from IOSequence:

+
+

+

Public Fields

+oint n_sequences +
+oint frame_size +

+ +

+

Public Methods

+ovirtual int getNumberOfFrames(int t) +
+ovirtual void getSequence(int t, Sequence* sequence) +
+ovirtual int getTotalNumberOfFrames() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
IOSequence which does a selection of adjacent columns +on another IOSequence, when calling getMatrix(). + +

+
+ + + +
o IOSub(IOBufferize* io_torch_, int offset_, int frame_size_) +
We will select columns indexed by offset_offset_+frame_size_-1 +of the frames provided by io_torch_, when calling getSequence() +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/InputsSelect.html b/torch3/manual/InputsSelect.html new file mode 100644 index 0000000..53c686f --- /dev/null +++ b/torch3/manual/InputsSelect.html @@ -0,0 +1,146 @@ + + + + + class InputsSelect + + + + +

class InputsSelect

Machine which select a block of adjacent inputs, and put them in the outputs.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] InputsSelect(int n_inputs_, int offset_, int n_selected_) +
Select n_selected_ inputs from offset_. +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Machine which select a block of adjacent +inputs, and put them in the outputs. + +

+
+ + + +
o InputsSelect(int n_inputs_, int offset_, int n_selected_) +
Select n_selected_ inputs from offset_. +(The input offset_ will be included). +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/IntCmdOption.html b/torch3/manual/IntCmdOption.html new file mode 100644 index 0000000..aed3f43 --- /dev/null +++ b/torch3/manual/IntCmdOption.html @@ -0,0 +1,128 @@ + + + + + class IntCmdOption + + + + +

class IntCmdOption

This class defines a integer command-line option.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] IntCmdOption(const char* name_, int* ptr_, int init_value_, const char* help_="", bool save_=false) +

+ +
+

Inherited from CmdOption:

+
+

+

Public Fields

+ochar* name +
+ochar* type_name +
+ochar* help +
+obool save +
+obool is_setted +

+ +

+

Public Methods

+ovirtual void initValue() +
+ovirtual void printValue(XFile* file_) +
+ovirtual void read(int* argc_, char*** argv_) +
+obool isOption(bool set_=false) +
+obool isArgument(bool set_=false) +
+obool isText(bool set_=false) +
+obool isMasterSwitch(bool set_=false) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class defines a integer command-line option. + +

+
+ + + +
o IntCmdOption(const char* name_, int* ptr_, int init_value_, const char* help_="", bool save_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/KFold.html b/torch3/manual/KFold.html new file mode 100644 index 0000000..a83b7a5 --- /dev/null +++ b/torch3/manual/KFold.html @@ -0,0 +1,157 @@ + + + + + class KFold + + + + +

class KFold

Provides an interface to sample data, for use by methods such as cross-validation
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int** train_subsets +
Training examples for each fold +
+[more]int** test_subsets +
Test examples for each fold +
+[more]int* n_train_subsets +
Number of training examples for each fold +
+[more]int* n_test_subsets +
Number of test examples for each fold +

+ +

+

Public Methods

+[more] KFold(Trainer* trainer_, int kfold_) +
+[more]virtual void crossValidate(DataSet* data, MeasurerList* train_measurers=NULL, MeasurerList* test_measurers=NULL, MeasurerList* cross_valid_measurers=NULL) +
Do a cross-validation over data. +
+[more]virtual void sample(int n_examples) +
Prepare the sample. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Provides an interface to sample data, for use by methods such +as cross-validation + +

+
+ + + +
oint** train_subsets +
Training examples for each fold +

+ + +

oint** test_subsets +
Test examples for each fold +

+ + +

oint* n_train_subsets +
Number of training examples for each fold +

+ + +

oint* n_test_subsets +
Number of test examples for each fold +

+ + +

o KFold(Trainer* trainer_, int kfold_) +

+ + +

ovirtual void crossValidate(DataSet* data, MeasurerList* train_measurers=NULL, MeasurerList* test_measurers=NULL, MeasurerList* cross_valid_measurers=NULL) +
Do a cross-validation over data. +train_measurers are called in each "train pass" for each fold. +test_measurers are called in each "test pass" for each fold. +cross_valid_measurers are called during the cross-validation loop. +

+ + +

ovirtual void sample(int n_examples) +
Prepare the sample. +Given n_examples, puts the right examples-indices in train_subsets +and test_subsets, and updates n_train_subsets and n_test_subsets. +(You don't have to allocate these arrays). +The provided sample function is a standard sample for cross-validation, +but you could imagine what you want! +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/KMeans.html b/torch3/manual/KMeans.html new file mode 100644 index 0000000..1a05dae --- /dev/null +++ b/torch3/manual/KMeans.html @@ -0,0 +1,274 @@ + + + + + class KMeans + + + + +

class KMeans

This class can be used to do a "kmeans" on a given set of data.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Sequence* min_cluster +
for each example, keep the index of the neirest cluster +

+ +

+

Public Methods

+[more] KMeans(int n_inputs, int n_gaussians_) +
+[more]virtual real frameLogProbability(int t, real* inputs) +
note that this method returns in fact the euclidean distance between the observation and the neirest cluster +
+[more]virtual real frameLogProbabilityOneGaussian(int g, real* inputs) +
similarly to frameLogProbability, this method returns the euclidean distance between cluster g and the given observation +

+ +

+

Public Members

+[more] initialize the parameters from the data set to false if you +

+ +
+

Inherited from DiagonalGMM:

+
+

+

Public Fields

+oint n_gaussians +
+oreal prior_weights +
+oEMTrainer* initial_kmeans_trainer +
+oMeasurerList* initial_kmeans_trainer_measurers +
+oreal* log_weights +
+oreal* dlog_weights +
+oreal* var_threshold +
+oSequence* log_probabilities_g +
+oint best_gauss +
+oSequence* best_gauss_per_frame +
+oreal* sum_log_var_plus_n_obs_log_2_pi +
+oreal** minus_half_over_var +
+oreal** means_acc +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* data_) +
+ovirtual void setVarThreshold(real* var_threshold_) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual real viterbiFrameLogProbability(int t, real* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void frameEMAccPosteriors(int t, real* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void frameDecision(int t, real* decision) +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to do a "kmeans" on a given set of data. +It has been implemented in the framework of a Distribution that can +be trained with EM. This means that the kmeans distance is in fact +returned by the method logProbability. + +

Note that as KMeans is a subclass of DiagonalGMM, they share the same +parameter structure. Hence, a DiagonalGMM can be easily initialized by +a KMeans. + +

+
+ + + +
oSequence* min_cluster +
for each example, keep the index of the neirest cluster +

+ + +

o initialize the parameters from the data set to false if you +
initialize the parameters from the data set to false if you +

+ + +

o KMeans(int n_inputs, int n_gaussians_) +

+ + +

ovirtual real frameLogProbability(int t, real* inputs) +
note that this method returns in fact the euclidean distance between +the observation and the neirest cluster +

+ + +

ovirtual real frameLogProbabilityOneGaussian(int g, real* inputs) +
similarly to frameLogProbability, this method returns the euclidean +distance between cluster g and the given observation +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/KNN.html b/torch3/manual/KNN.html new file mode 100644 index 0000000..2de6c76 --- /dev/null +++ b/torch3/manual/KNN.html @@ -0,0 +1,176 @@ + + + + + class KNN + + + + +

class KNN

This machine implements the K-nearest-neighbors (KNN) algorithm.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int K +
The number of nearest neighbors. +
+[more]real* distances +
For each nearest neighbor, keeps its distance to the current input +
+[more]int* indices +
For each nearest neighbor, keeps its index in the dataset +
+[more]DataSet* data +
The dataset that contains the potential neaghbors +
+[more]int n_outputs +
the size of the output vector +
+[more]int* real_examples +
the indices of the training examples +

+ +

+

Public Methods

+[more] KNN(int n_outputs_, int K_) +
+[more]virtual void setK(int K_) +
change the value of K +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This machine implements the K-nearest-neighbors (KNN) algorithm. +Given a dataset (in the constructor), the forward method returns +for a given input the average of the outputs of the K nearest examples +(in the input space, using the Euclidean distance). As a side effect, +the machine also keep the table of distances of the K-nearest-neighbors. + +

+
+ + + +
oint K +
The number of nearest neighbors. Controls the capacity of the machine +

+ + +

oreal* distances +
For each nearest neighbor, keeps its distance to the current input +

+ + +

oint* indices +
For each nearest neighbor, keeps its index in the dataset +

+ + +

oDataSet* data +
The dataset that contains the potential neaghbors +

+ + +

oint n_outputs +
the size of the output vector +

+ + +

oint* real_examples +
the indices of the training examples +

+ + +

o KNN(int n_outputs_, int K_) +

+ + +

ovirtual void setK(int K_) +
change the value of K +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Kernel.html b/torch3/manual/Kernel.html new file mode 100644 index 0000000..94e3d06 --- /dev/null +++ b/torch3/manual/Kernel.html @@ -0,0 +1,112 @@ + + + + + class Kernel + + + + +

class Kernel

General Kernel class.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Kernel() +
+[more]virtual real eval(Sequence* x, Sequence* y) = 0 +
Compute kernel between the example x and y +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
General Kernel class. +Kernels are applied on two sequences with the method eval(). +Actually, usual kernels (given here) don't use sequences, +but the first frame of each sequences... + +

+
+ + + +
o Kernel() +

+ + +

ovirtual real eval(Sequence* x, Sequence* y) = 0 +
Compute kernel between the example x and y +

+
+
Direct child classes: +
SigmoidKernel
+PolynomialKernel
+GaussianKernel
+DotKernel
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LMCache.html b/torch3/manual/LMCache.html new file mode 100644 index 0000000..7e1ef62 --- /dev/null +++ b/torch3/manual/LMCache.html @@ -0,0 +1,131 @@ + + + + + class LMCache + + + + +

class LMCache

This class implements a rudimentary caching scheme for language model lookup.
+
+ +
+

+

Public Members

+[more] Creates an empty cache +
+[more] 'max_entries_' is the maximum number of entries in the cache +
+[more] 'lm_order' is the order of the language model n-gram (ie 3 +
+[more] for a trigram LM) +
+[more] Adds an entry to the cache. +
+[more] entry is not already in the cache, the oldest entry is +
+[more] overwritten +
+[more] 'order' is the order of the entry, which can be <= the lm_order +
+[more] used during cache creation +
+[more] 'words' are the words in the n-gram. +
+[more] for a 4-gram entry +
+[more] 'prob' is the log probability of the n-gram as calculated by the +
+[more] Looks for the n-gram in 'words' within the cache and returns +

+ +
+ + +
+

Documentation

+
+This class implements a rudimentary caching scheme for language +model lookup. It basically consists of a (small) list of the most +recently accessed language model entries. A cache lookup entails +a linear search of the list of entries. The oldest entry is +overwritten when the cache is full and a new entry is added. + +

+
+ + + +
o Creates an empty cache +
Creates an empty cache +

+ + +

o 'max_entries_' is the maximum number of entries in the cache +
'max_entries_' is the maximum number of entries in the cache +

+ + +

o 'lm_order' is the order of the language model n-gram (ie 3 +
'lm_order' is the order of the language model n-gram (ie 3 +

+ + +

o for a trigram LM) +
for a trigram LM) +

+ + +

o Adds an entry to the cache. +
Adds an entry to the cache. If the cache is full and the new +

+ + +

o entry is not already in the cache, the oldest entry is +
entry is not already in the cache, the oldest entry is +

+ + +

o overwritten +
overwritten +

+ + +

o 'order' is the order of the entry, which can be <= the lm_order +
'order' is the order of the entry, which can be <= the lm_order +

+ + +

o used during cache creation +
used during cache creation +

+ + +

o 'words' are the words in the n-gram. +
'words' are the words in the n-gram. The order is W3 W2 W1 W4 +

+ + +

o for a 4-gram entry +
for a 4-gram entry +

+ + +

o 'prob' is the log probability of the n-gram as calculated by the +
'prob' is the log probability of the n-gram as calculated by the +

+ + +

o Looks for the n-gram in 'words' within the cache and returns +
Looks for the n-gram in 'words' within the cache and returns +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LMCacheEntry.html b/torch3/manual/LMCacheEntry.html new file mode 100644 index 0000000..882e016 --- /dev/null +++ b/torch3/manual/LMCacheEntry.html @@ -0,0 +1,101 @@ + + + + + class LMCacheEntry + + + + +

class LMCacheEntry

This class implements the internal entries within the LMCache class.
+
+ +
+

+

Public Methods

+[more]void addProb( int vocab_word, real prob ) +
Adds a log probability for the next-word denoted by 'vocab_word' +

+ +

+

Public Members

+[more] Creates the cache entry +
+[more] 'max_n_prev_words_' is the maximum number of prev words that will +
+[more] ever be used with the cache entry (eg. +
+[more] Replaces the current prev words with new ones. +
+[more] a number of prev words that is <= max_n_prev_words (ie. +
+[more] Resets all of the next-word log probs to -LOG_ZERO (to indicate that +
+[more] Returns the cached log probability for the next-word denoted by +

+ +
+ + +
+

Documentation

+
+This class implements the internal entries within the LMCache +class. Each entry consists of an array of previous words (eg. +2 previous words in a trigram entry), and a list of probabilities +of next words given the previous words. There is also an age +field that is used to keep track of how recently the entry was +accessed. + +

+
+ + + +
o Creates the cache entry +
Creates the cache entry +

+ + +

o 'max_n_prev_words_' is the maximum number of prev words that will +
'max_n_prev_words_' is the maximum number of prev words that will +

+ + +

o ever be used with the cache entry (eg. +
ever be used with the cache entry (eg. 2 for trigram LM) +

+ + +

o Replaces the current prev words with new ones. +
Replaces the current prev words with new ones. The new entry can +

+ + +

o a number of prev words that is <= max_n_prev_words (ie. +
a number of prev words that is <= max_n_prev_words (ie. can +

+ + +

o Resets all of the next-word log probs to -LOG_ZERO (to indicate that +
Resets all of the next-word log probs to -LOG_ZERO (to indicate that +

+ + +

ovoid addProb( int vocab_word, real prob ) +
Adds a log probability for the next-word denoted by 'vocab_word' +

+ + +

o Returns the cached log probability for the next-word denoted by +
Returns the cached log probability for the next-word denoted by +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LMInteriorLevelWordEntry.html b/torch3/manual/LMInteriorLevelWordEntry.html new file mode 100644 index 0000000..d29c1cd --- /dev/null +++ b/torch3/manual/LMInteriorLevelWordEntry.html @@ -0,0 +1,30 @@ + + + + + class LMInteriorLevelWordEntry + + + + +

class LMInteriorLevelWordEntry

This class is used internally within the language model n-gram data structures.
+ + +
+

Documentation

+
+This class is used internally within the language model n-gram +data structures. It contains a list of LM probabilities relevant +to the level of the tree structure where it exists, and a link to +the next level of the tree structure. + +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LMInteriorLevelWordList.html b/torch3/manual/LMInteriorLevelWordList.html new file mode 100644 index 0000000..76b2fa7 --- /dev/null +++ b/torch3/manual/LMInteriorLevelWordList.html @@ -0,0 +1,146 @@ + + + + + class LMInteriorLevelWordList + + + + +

class LMInteriorLevelWordList


+ +
+

+

Public Methods

+[more]LMInteriorLevelWordEntry* findWord( int word ) +
Internal function +

+ +

+

Public Members

+[more] Creates the list. +
+[more] levels in the tree-like n-gram data structures. +
+[more] Adds a language model probability. +
+[more] Adds a language model backoff weight. +
+[more] of the entry that is being added, and 'words' contains the +
+[more] vocabulary indices of the words in the n-gram. +
+[more] of 'words' should be eg. +
+[more] Calculates a language model probability for a particular word +
+[more] sequence with backoff. +
+[more] in the word sequence, and 'words' contains the vocabulary +
+[more] indices of the words. +
+[more] eg. +
+[more] "most-recent" word. +
+[more] indicating that the value of prob contains only an +
+[more] accumulated backoff weight. +

+ +
+ + +
+

Documentation

+
+ + + +
o Creates the list. +
Creates the list. Instances of this object are used at different +

+ + +

o levels in the tree-like n-gram data structures. +
levels in the tree-like n-gram data structures. +

+ + +

o Adds a language model probability. +
Adds a language model probability. 'order' denotes the order +

+ + +

o Adds a language model backoff weight. +
Adds a language model backoff weight. 'order' denotes the order +

+ + +

o of the entry that is being added, and 'words' contains the +
of the entry that is being added, and 'words' contains theof the entry that is being added, and 'words' contains the +

+ + +

o vocabulary indices of the words in the n-gram. +
vocabulary indices of the words in the n-gram. The orderingvocabulary indices of the words in the n-gram. The ordering +

+ + +

o of 'words' should be eg. +
of 'words' should be eg. W4,W3,W2,W1 when 'order' is 4 andof 'words' should be eg. W3,W2,W1,W4 when 'order' is 4 and +

+ + +

o Calculates a language model probability for a particular word +
Calculates a language model probability for a particular word +

+ + +

o sequence with backoff. +
sequence with backoff. 'order' denotes the number of words +

+ + +

o in the word sequence, and 'words' contains the vocabulary +
in the word sequence, and 'words' contains the vocabulary +

+ + +

o indices of the words. +
indices of the words. The ordering of 'words' should be +

+ + +

o eg. +
eg. W3,W2,W1,W4 when 'order' is 4 and where W4 is the +

+ + +

o "most-recent" word. +
"most-recent" word. Returns false if no entry was found, +

+ + +

o indicating that the value of prob contains only an +
indicating that the value of prob contains only an +

+ + +

o accumulated backoff weight. +
accumulated backoff weight. Returns true if a valid +

+ + +

oLMInteriorLevelWordEntry* findWord( int word ) +
Internal function +

+ +
This class has no child classes.
+ +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LMNGram.html b/torch3/manual/LMNGram.html new file mode 100644 index 0000000..8e2a2d2 --- /dev/null +++ b/torch3/manual/LMNGram.html @@ -0,0 +1,154 @@ + + + + + class LMNGram + + + + +

class LMNGram

This class is the main class for N-gram language modelling.
+
+ +
+

+

Public Fields

+[more]int n +
The order of the N-Gram +
+[more]real* unigrams +
The unigram probability entries, 1 for every vocab word +
+[more]LMInteriorLevelWordList* next_level +
Points to the start of the language model tree structure +
+[more]LMCache* cache +
The cache used for fast LM lookup +

+ +

+

Public Methods

+[more] LMNGram( int n_, Vocabulary* vocab_ ) +
Creates an empty N-Gram data structure. +

+ +

+

Public Members

+[more] Adds a new entry to the N-gram +
+[more] 'order' is the order of the entry (ie. +
+[more] The 'words' array needs to be in oldest-word-first order +
+[more] ([w1 w2 w3] for trigram entry) +
+[more] 'prob' is the log probability for the entry +
+[more] 'bo_wt' is the log back-off weight for the entry. +
+[more] Finds the N-gram probability of a given word sequence, with full +
+[more] backoff +
+[more] 'order' is the number of words in the 'words' array +
+[more] The ordering in 'words' is W3,W2,W1,W4 for a 4-gram query +

+ +
+ + +
+

Documentation

+
+This class is the main class for N-gram language modelling. +After language model entries have been added, lookups with full +backoff can be performed. + +

+
+ + + +
oint n +
The order of the N-Gram +

+ + +

oreal* unigrams +
The unigram probability entries, 1 for every vocab word +

+ + +

oLMInteriorLevelWordList* next_level +
Points to the start of the language model tree structure +

+ + +

oLMCache* cache +
The cache used for fast LM lookup +

+ + +

o LMNGram( int n_, Vocabulary* vocab_ ) +
Creates an empty N-Gram data structure. 'n_' is the N-gram order. +

+ + +

o Adds a new entry to the N-gram +
Adds a new entry to the N-gram +

+ + +

o 'order' is the order of the entry (ie. +
'order' is the order of the entry (ie. 2 for a bigram entry). +

+ + +

o The 'words' array needs to be in oldest-word-first order +
The 'words' array needs to be in oldest-word-first order +

+ + +

o ([w1 w2 w3] for trigram entry) +
([w1 w2 w3] for trigram entry) +

+ + +

o 'prob' is the log probability for the entry +
'prob' is the log probability for the entry +

+ + +

o 'bo_wt' is the log back-off weight for the entry. +
'bo_wt' is the log back-off weight for the entry. If order is +

+ + +

o Finds the N-gram probability of a given word sequence, with full +
Finds the N-gram probability of a given word sequence, with full +

+ + +

o backoff +
backoff +

+ + +

o 'order' is the number of words in the 'words' array +
'order' is the number of words in the 'words' array +

+ + +

o The ordering in 'words' is W3,W2,W1,W4 for a 4-gram query +
The ordering in 'words' is W3,W2,W1,W4 for a 4-gram query +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LanguageModel.html b/torch3/manual/LanguageModel.html new file mode 100644 index 0000000..b8c1e1c --- /dev/null +++ b/torch3/manual/LanguageModel.html @@ -0,0 +1,86 @@ + + + + + class LanguageModel + + + + +

class LanguageModel

This object implements an n-gram language model.
+
+ +
+

+

Public Methods

+[more]void readARPA( FILE* arpa_fd ) +
Creates a language model from an ARPA format file. +

+ +

+

Public Members

+[more] Creates the language model. +
+[more] Calculates the language model probability (with backoff) of the word +
+[more] Calculates the language model probability (with backoff) of 'next_word' +
+[more] given the previous word sequence stored in the hypothesis pointed to +
+[more] Creates a language model from an Noway binary LM format file. +

+ +
+ + +
+

Documentation

+
+This object implements an n-gram language model. The n-gram data structures +are encapsulated in the ngram member variable (see LMNGram class). Methods +are provided to read a LM file in ARPA format or in Noway binary format. +A method is provided to calculate a LM prob (with backoff) for a given +sequence of words. + +

+
+ + + +
o Creates the language model. +
Creates the language model. +

+ + +

o Calculates the language model probability (with backoff) of the word +
Calculates the language model probability (with backoff) of the word +

+ + +

o Calculates the language model probability (with backoff) of 'next_word' +
Calculates the language model probability (with backoff) of 'next_word' +

+ + +

o given the previous word sequence stored in the hypothesis pointed to +
given the previous word sequence stored in the hypothesis pointed to +

+ + +

ovoid readARPA( FILE* arpa_fd ) +
Creates a language model from an ARPA format file. Internal function. +

+ + +

o Creates a language model from an Noway binary LM format file. +
Creates a language model from an Noway binary LM format file. Internal function. +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LexiconInfo.html b/torch3/manual/LexiconInfo.html new file mode 100644 index 0000000..6348dc6 --- /dev/null +++ b/torch3/manual/LexiconInfo.html @@ -0,0 +1,123 @@ + + + + + class LexiconInfo + + + + +

class LexiconInfo

This class stores information about how phonemes are assembled into pronunciations.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Members

+[more] Creates a LexiconInfo instance. +
+[more] PhoneInfo instance (see PhoneInfo header). +
+[more] create a Vocabulary instance and then to create pronunciation +
+[more] entries and the mapping between Vocabulary entries and pronunciation +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
+This class stores information about how phonemes are assembled +into pronunciations. For each pronunciation, a list of indices +into a PhoneInfo instance is stored, along with a prior and a +index into a Vocabulary instance. Information is also stored to +map Vocabulary entries to one or more pronunciations. + +

+
+ + + +
o Creates a LexiconInfo instance. +
Creates a LexiconInfo instance. 'phones_fname' is used to create a +

+ + +

o PhoneInfo instance (see PhoneInfo header). +
PhoneInfo instance (see PhoneInfo header). 'lex_fname' is used to +

+ + +

o create a Vocabulary instance and then to create pronunciation +
create a Vocabulary instance and then to create pronunciation +

+ + +

o entries and the mapping between Vocabulary entries and pronunciation +
entries and the mapping between Vocabulary entries and pronunciation +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Linear.html b/torch3/manual/Linear.html new file mode 100644 index 0000000..df23c1b --- /dev/null +++ b/torch3/manual/Linear.html @@ -0,0 +1,160 @@ + + + + + class Linear + + + + +

class Linear

Linear layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Linear(int n_inputs_, int n_outputs_) +
+[more]virtual void reset() +
Computes new random values for weights +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Linear layer for GradientMachine. +Formally speaking, .
+ and are in params, with the following structure:
+
+ +

If you want, you can add a weight decay which looks like +. + +

Options: + +
+"weight decay" real the weight decay [0] +
+ +

+
+ + + +
o Linear(int n_inputs_, int n_outputs_) +

+ + +

ovirtual void reset() +
Computes new random values for weights +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LinearLexicon.html b/torch3/manual/LinearLexicon.html new file mode 100644 index 0000000..70a1912 --- /dev/null +++ b/torch3/manual/LinearLexicon.html @@ -0,0 +1,110 @@ + + + + + class LinearLexicon + + + + +

class LinearLexicon

This class is essentially an array of DecodingHMM instances, representing the HMM's for each pronunciation we can recognise.
+
+ +
+

+

Public Members

+[more] Uses the phoneme DecodingHMM instances in 'phone_models_', +
+[more] and the phonetic transcription info for the pronunciations +
+[more] as defined in 'lex_info_' and creates a complete DecodingHMM +
+[more] Extracts LexiconInfo pointer from 'speech_hmm' then proceeds +
+[more] Internal function. +
+[more] Returns the number of states in a particular model including +
+[more] Calculates the emission probability for a state in a particular +
+[more] word model using the current input vector. +
+[more] Returns the number of successor states, the successor states +
+[more] themselves and the associated log transition probabilities +

+ +
+ + +
+

Documentation

+
+This class is essentially an array of DecodingHMM instances, +representing the HMM's for each pronunciation we can recognise. +The ordering of this array conforms to the ordering the +LexInfo instance that is passed as a parameter to the +constructor. + +

+
+ + + +
o Uses the phoneme DecodingHMM instances in 'phone_models_', +
Uses the phoneme DecodingHMM instances in 'phone_models_', +

+ + +

o and the phonetic transcription info for the pronunciations +
and the phonetic transcription info for the pronunciations +

+ + +

o as defined in 'lex_info_' and creates a complete DecodingHMM +
as defined in 'lex_info_' and creates a complete DecodingHMM +

+ + +

o Extracts LexiconInfo pointer from 'speech_hmm' then proceeds +
Extracts LexiconInfo pointer from 'speech_hmm' then proceeds +

+ + +

o Internal function. +
Internal function. Both constructors call this to create the +

+ + +

o Returns the number of states in a particular model including +
Returns the number of states in a particular model including +

+ + +

o Calculates the emission probability for a state in a particular +
Calculates the emission probability for a state in a particular +

+ + +

o word model using the current input vector. +
word model using the current input vector. Only checks for +

+ + +

o Returns the number of successor states, the successor states +
Returns the number of successor states, the successor states +

+ + +

o themselves and the associated log transition probabilities +
themselves and the associated log transition probabilities +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/List.html b/torch3/manual/List.html new file mode 100644 index 0000000..3629960 --- /dev/null +++ b/torch3/manual/List.html @@ -0,0 +1,55 @@ + + + + + class List + + + + +

class List

+
List Classes. + +

A list named NAME with node pointer type TYPE has the following aspect: + +

+class NAME
+{
+  /// Pointer which can be used as you want.
+  TYPE *nodes;
+  
+  /// Number of nodes.
+  int n_nodes;
+
+  /// Constructor.
+  NAME();
+
+  /// Add a list at the end of the current list.
+  void add(NAME *list);
+
+  /// Add a node at the end of the current list.
+  void addNode(TYPE *node_)
+};
+
+ +

To declare a new list, just use the macro (in ".h" files): + +

+#DEFINE_NEW_LIST(NAME, TYPE);
+
+ +

and to implement this list, use the macro (in ".cc" files): +

+#define IMPLEMENT_NEW_LIST(NAME, TYPE)
+
+ +

The name of a list which TYPE nodes should be something like "TYPEList". + +

+
Author:
Ronan Collobert (collober@idiap.ch) + +

Alphabetic index Hierarchy of classes


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LogMixer.html b/torch3/manual/LogMixer.html new file mode 100644 index 0000000..d412f7e --- /dev/null +++ b/torch3/manual/LogMixer.html @@ -0,0 +1,154 @@ + + + + + class LogMixer + + + + +

class LogMixer

LogMixer useful for experts mixtures.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] LogMixer(int n_inputs_, int n_outputs_per_expert) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
LogMixer useful for experts mixtures. +Formally speaking, it computes: + + +

where +

    +
  • are the first n_experts inputs +of the machine. + +

  • are the outputs of the j-th expert. +Therefore, the inputs given to the machine have the following structure: +. +
+ +

+
+ + + +
o LogMixer(int n_inputs_, int n_outputs_per_expert) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LogRBF.html b/torch3/manual/LogRBF.html new file mode 100644 index 0000000..c683fc2 --- /dev/null +++ b/torch3/manual/LogRBF.html @@ -0,0 +1,160 @@ + + + + + class LogRBF + + + + +

class LogRBF

LogRBF layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]EMTrainer* initial_kmeans_trainer +
optional initialization using a Kmeans +

+ +

+

Public Methods

+[more] LogRBF(int n_inputs_, int n_outputs_, EMTrainer* kmeans_trainer=NULL) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
LogRBF layer for GradientMachine. +Formally speaking, .
+ and are in params, with the following structure:
+
+ +

For a better initialization, one can provide a EMTrainer using a +Kmeans distribution that will be used to initialize the means and +gamma. + +

+
+ + + +
oEMTrainer* initial_kmeans_trainer +
optional initialization using a Kmeans +

+ + +

o LogRBF(int n_inputs_, int n_outputs_, EMTrainer* kmeans_trainer=NULL) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LogSigmoid.html b/torch3/manual/LogSigmoid.html new file mode 100644 index 0000000..3bb93fe --- /dev/null +++ b/torch3/manual/LogSigmoid.html @@ -0,0 +1,147 @@ + + + + + class LogSigmoid + + + + +

class LogSigmoid

Log-Sigmoid layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] LogSigmoid(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Log-Sigmoid layer for GradientMachine. +The number of inputs/outputs is the number +of units of this machine. +Formally speaking, + +

+
+ + + +
o LogSigmoid(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/LogSoftMax.html b/torch3/manual/LogSoftMax.html new file mode 100644 index 0000000..b944d10 --- /dev/null +++ b/torch3/manual/LogSoftMax.html @@ -0,0 +1,150 @@ + + + + + class LogSoftMax + + + + +

class LogSoftMax

Log-SoftMax layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] LogSoftMax(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Log-SoftMax layer for GradientMachine. + +

The number of inputs/outputs is the number +of units in the machine. + +

Formally speaking, +where . + +

+
+ + + +
o LogSoftMax(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MAPDiagonalGMM.html b/torch3/manual/MAPDiagonalGMM.html new file mode 100644 index 0000000..29dcb60 --- /dev/null +++ b/torch3/manual/MAPDiagonalGMM.html @@ -0,0 +1,307 @@ + + + + + class MAPDiagonalGMM + + + + +

class MAPDiagonalGMM

This class is a special case of a DiagonalGMM that implements the MAP algorithm instead of the EM algorithm.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]DiagonalGMM* prior_distribution +
The prior distribution used in MAP +
+[more]real weight_on_prior +
The weight to give to the prior parameters during update +
+[more]bool learn_weights +
update Gaussian's weights +
+[more]bool learn_variances +
update Gaussian's variances +
+[more]bool learn_means +
update Gaussian's means +

+ +

+

Public Methods

+[more] MAPDiagonalGMM(DiagonalGMM* prior_distribution_) +
+[more]virtual void frameViterbiAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of Viterbi for a frame +
+[more]virtual void frameEMAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of EM for a frame +
+[more]virtual void eMUpdate() +
The update after each iteration for EM +
+[more]virtual void setDataSet(DataSet* data_) +
Copy the parameters of the prior distribution +

+ +
+

Inherited from DiagonalGMM:

+
+

+

Public Fields

+oint n_gaussians +
+oreal prior_weights +
+oEMTrainer* initial_kmeans_trainer +
+oMeasurerList* initial_kmeans_trainer_measurers +
+oreal* log_weights +
+oreal* dlog_weights +
+oreal* var_threshold +
+oSequence* log_probabilities_g +
+oint best_gauss +
+oSequence* best_gauss_per_frame +
+oreal* sum_log_var_plus_n_obs_log_2_pi +
+oreal** minus_half_over_var +
+oreal** means_acc +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setVarThreshold(real* var_threshold_) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual real frameLogProbability(int t, real* inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* inputs) +
+ovirtual real frameLogProbabilityOneGaussian(int g, real* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void update() +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void frameDecision(int t, real* decision) +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class is a special case of a DiagonalGMM that implements the +MAP algorithm instead of the EM algorithm. This means that the +mean parameters will be changed according to the Maximum A Posteriori +algorithm, given a prior value of the means (through a prior DiagonalGMM +given in the constructor). Moreover, the variances and weights are +not changed, as experimental results tend to show that there is no +effects when they are changed. + +

+
+ + + +
oDiagonalGMM* prior_distribution +
The prior distribution used in MAP +

+ + +

oreal weight_on_prior +
The weight to give to the prior parameters during update +

+ + +

obool learn_weights +
update Gaussian's weights +

+ + +

obool learn_variances +
update Gaussian's variances +

+ + +

obool learn_means +
update Gaussian's means +

+ + +

o MAPDiagonalGMM(DiagonalGMM* prior_distribution_) +

+ + +

ovirtual void frameViterbiAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of Viterbi for a frame +

+ + +

ovirtual void frameEMAccPosteriors(int t, real* inputs, real log_posterior) +
The backward step of EM for a frame +

+ + +

ovirtual void eMUpdate() +
The update after each iteration for EM +

+ + +

ovirtual void setDataSet(DataSet* data_) +
+Copy the parameters of the prior distribution +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MAPHMM.html b/torch3/manual/MAPHMM.html new file mode 100644 index 0000000..3069091 --- /dev/null +++ b/torch3/manual/MAPHMM.html @@ -0,0 +1,288 @@ + + + + + class MAPHMM + + + + +

class MAPHMM

This class is a special case of a HMM that implements the MAP algorithm for HMM transitions probabilities.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]HMM* prior_distribution +
The prior distribution used in MAP +
+[more]real weight_on_prior +
The weight to give to the prior parameters during update +
+[more]real log_weight_on_prior +
log(weight_on_prior) +
+[more]real log_1_weight_on_prior +
log(1-weight_on_prior_ +

+ +

+

Public Methods

+[more] MAPHMM(int n_states_, Distribution** states_, real** transitions_, HMM* prior_distribution_) +
+[more]virtual void eMUpdate() +
map adaptation method for transitions probabilities +

+ +
+

Inherited from HMM:

+
+

+

Public Fields

+oint n_states +
+oreal prior_transitions +
+oDistribution** states +
+oDistribution** shared_states +
+oreal** transitions +
+oreal** log_transitions +
+oreal** dlog_transitions +
+oreal** transitions_acc +
+oSequence* log_alpha +
+oSequence* log_beta +
+oSequence* arg_viterbi +
+oint last_arg_viterbi +
+oSequence* viterbi_sequence +
+oSequence* log_probabilities_s +
+obool initialize +

+ +

+

Public Methods

+ovirtual void printTransitions(bool real_values=false, bool transitions_only=false) +
+ovirtual void logAlpha(Sequence* inputs) +
+ovirtual void logBeta(Sequence* inputs) +
+ovirtual void logViterbi(Sequence* inputs) +
+ovirtual void decode(Sequence* input) +
+ovirtual void logProbabilities(Sequence* inputs) +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void update() +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class is a special case of a HMM that implements the +MAP algorithm for HMM transitions probabilities. + +

+
+ + + +
oHMM* prior_distribution +
The prior distribution used in MAP +

+ + +

oreal weight_on_prior +
The weight to give to the prior parameters during update +

+ + +

oreal log_weight_on_prior +
log(weight_on_prior) +

+ + +

oreal log_1_weight_on_prior +
log(1-weight_on_prior_ +

+ + +

o MAPHMM(int n_states_, Distribution** states_, real** transitions_, HMM* prior_distribution_) +

+ + +

ovirtual void eMUpdate() +
map adaptation method for transitions probabilities +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +Johnny Mariethoz (marietho@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MLP.html b/torch3/manual/MLP.html new file mode 100644 index 0000000..84cb362 --- /dev/null +++ b/torch3/manual/MLP.html @@ -0,0 +1,175 @@ + + + + + class MLP + + + + +

class MLP

A Multi-Layer Perceptron.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] MLP(int n_layers, int n_inputs_, ...) +
Create a MLP with n_layers layers and n_inputs_ inputs. +
+[more]void setWeightDecay(real weight_decay) +
Set the weight decay in all Linear layers +

+ +
+

Inherited from ConnectedMachine:

+
+

+

Public Methods

+ovoid addFCL(GradientMachine* machine) +
+ovoid addMachine(GradientMachine* machine) +
+ovoid connectOn(GradientMachine* machine) +
+ovoid addLayer() +
+ovoid build() +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A Multi-Layer Perceptron. + +

+
+ + + +
o MLP(int n_layers, int n_inputs_, ...) +
Create a MLP with n_layers layers and n_inputs_ inputs. +The definitions of the layer come then: it's a string +followed by an integer for the number of outputs of the layer. +Valid strings are "linear", "tanh", "sigmoid", "softmax", "log-softmax", +"exp" and "softplus". + +

Example: to create an MLP with one linear layer and one softmax layer, +MLP(2, n_inputs, "linear", n_outputs, "softmax", n_outputs); +

+ + +

ovoid setWeightDecay(real weight_decay) +
Set the weight decay in all Linear layers +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MSECriterion.html b/torch3/manual/MSECriterion.html new file mode 100644 index 0000000..1457d95 --- /dev/null +++ b/torch3/manual/MSECriterion.html @@ -0,0 +1,167 @@ + + + + + class MSECriterion + + + + +

class MSECriterion

Mean Squared Error criterion.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] MSECriterion(int n_inputs_) +
n_inputs_ is the input frame size +

+ +
+

Inherited from Criterion:

+
+

+

Public Fields

+oDataSet* data +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* data_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Mean Squared Error criterion. +Compute the MSE between its inputs and, +the targets of its associated DataSet. + +

The number of target frames in DataSet must +correspond to the number of input frames given +to this criterion. + +

Options: + +
+"average frame size" bool divided by the frame size [true] +
+ +

+
+ + + +
o MSECriterion(int n_inputs_) +
n_inputs_ is the input frame size +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MSEMeasurer.html b/torch3/manual/MSEMeasurer.html new file mode 100644 index 0000000..1c7844d --- /dev/null +++ b/torch3/manual/MSEMeasurer.html @@ -0,0 +1,133 @@ + + + + + class MSEMeasurer + + + + +

class MSEMeasurer

Mean Squared Error measurer.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] MSEMeasurer(Sequence* inputs_, DataSet* data_, XFile* file_) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Mean Squared Error measurer. +Compute the MSE between its inputs, +and the targets of its associated DataSet. + +

addBOption("average examples", &average_examples, true, "divided by the number of examples"); +addBOption("average frame size", &average_frame_size, true, "divided by the frame size"); +addBOption("average frames", &average_frames, true, "divided by the number of frames"); + +

Options: + +
+"average examples" bool divided by the number of examples [true]
+"average frame size" bool divided by the frame size [true]
+"average frames" bool divided by the number of frames [true] +
+ +

+
+ + + +
o MSEMeasurer(Sequence* inputs_, DataSet* data_, XFile* file_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Machine.html b/torch3/manual/Machine.html new file mode 100644 index 0000000..f0660c1 --- /dev/null +++ b/torch3/manual/Machine.html @@ -0,0 +1,141 @@ + + + + + class Machine + + + + +

class Machine

Object which can compute some outputs, given some inputs.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Sequence* outputs +
The outputs of the machine +

+ +

+

Public Methods

+[more] Machine() +
+[more]virtual void forward(Sequence* sequence) = 0 +
Given a sequence, update outputs +
+[more]virtual void reset() +
Reset the machine +
+[more]virtual void setDataSet(DataSet* dataset_) +
Some machine depends on a dataset. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Object which can compute some outputs, +given some inputs. + +

+
+ + + +
oSequence* outputs +
The outputs of the machine +

+ + +

o Machine() +

+ + +

ovirtual void forward(Sequence* sequence) = 0 +
Given a sequence, update outputs +

+ + +

ovirtual void reset() +
Reset the machine +

+ + +

ovirtual void setDataSet(DataSet* dataset_) +
Some machine depends on a dataset. +The trainer has to call this function when changing +the dataset. +

+
+
Direct child classes: +
WeightedSumMachine
+QCMachine
+ParzenMachine
+KNN
+GradientMachine
+BayesClassifierMachine
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Mat.html b/torch3/manual/Mat.html new file mode 100644 index 0000000..a8d6f66 --- /dev/null +++ b/torch3/manual/Mat.html @@ -0,0 +1,232 @@ + + + + + class Mat + + + + +

class Mat

Matrix object.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int m +
Size of the matrix +
+[more]real** ptr +
Data of the matrix +
+[more]real* base +
NULL if not allocated by Mat. +

+ +

+

Public Methods

+[more] Mat(real** ptr_, int n_rows, int n_cols) +
Create a matrix from values in ptr_. +
+[more] Mat(real* ptr_, int n_rows, int n_cols) +
Create a matrix from values in ptr_. +
+[more] Mat(int n_rows, int n_cols) +
Create a new matrix +
+[more]void copy(Mat* mat) +
Copy the matrix mat +
+[more]void zero() +
Zero the matrix +
+[more]real norm1() +
Compute the norm1 +
+[more]real normFrobenius() +
Compute the Frobenius norm +
+[more]real normInf() +
Compute the norm inf +
+[more]Vec* getRow(int row, Vec* vec = NULL) +
Return the row row of the matrix. +
+[more]Vec* getCol(int col, Vec* vec = NULL) +
Return the column col of the matrix. +
+[more]void setRow(int row, Vec* vec) +
Set the row row to values in vec +
+[more]void setCol(int row, Vec* vec) +
Set the column col to values in vec +
+[more]Mat* subMat(int row1, int col1, int row2, int col2) +
Return a sub-matrix. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Matrix object. + +

+
+ + + +
oint m +
Size of the matrix +

+ + +

oreal** ptr +
Data of the matrix +

+ + +

oreal* base +
NULL if not allocated by Mat. +(when you're using the first constructor of Mat, or for +the matrix returned by subMat) +

+ + +

o Mat(real** ptr_, int n_rows, int n_cols) +
Create a matrix from values in ptr_. +(No memory copy). +

+ + +

o Mat(real* ptr_, int n_rows, int n_cols) +
Create a matrix from values in ptr_. +(No memory copy). +

+ + +

o Mat(int n_rows, int n_cols) +
Create a new matrix +

+ + +

ovoid copy(Mat* mat) +
Copy the matrix mat +

+ + +

ovoid zero() +
Zero the matrix +

+ + +

oreal norm1() +
Compute the norm1 +

+ + +

oreal normFrobenius() +
Compute the Frobenius norm +

+ + +

oreal normInf() +
Compute the norm inf +

+ + +

oVec* getRow(int row, Vec* vec = NULL) +
Return the row row of the matrix. +If vec is NULL, return a new vector. +Else copy the row in vec. +

+ + +

oVec* getCol(int col, Vec* vec = NULL) +
Return the column col of the matrix. +If vec is NULL, return a new vector. +Else copy the column in vec. +

+ + +

ovoid setRow(int row, Vec* vec) +
Set the row row to values in vec +

+ + +

ovoid setCol(int row, Vec* vec) +
Set the column col to values in vec +

+ + +

oMat* subMat(int row1, int col1, int row2, int col2) +
Return a sub-matrix. +Note that the memory is shared with the original +matrix, so *be carefull*. +You have to destroy the returned matrix. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MatDataSet.html b/torch3/manual/MatDataSet.html new file mode 100644 index 0000000..c12724b --- /dev/null +++ b/torch3/manual/MatDataSet.html @@ -0,0 +1,187 @@ + + + + + class MatDataSet + + + + +

class MatDataSet

Matrix DataSet.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] MatDataSet(const char* filename, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Create a new dataset from the file filename. +
+[more] MatDataSet(char** filenames, int n_files_, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Same as the previous constructor, but for several files. +
+[more] MatDataSet(char** input_filenames, char** target_filenames, int n_files_, int max_load=-1, bool binary_mode=false) +
Here the inputs and the targets are in separated files. +

+ +
+

Inherited from MemoryDataSet:

+
+

+

Public Fields

+oSequence** inputs_array +
+oSequence** targets_array +

+ +

+

Public Methods

+ovoid init(IOSequence* io_inputs, IOSequence* io_outputs) +
+ovoid setInputs(Sequence** inputs_, int n_sequences_) +
+ovoid setTargets(Sequence** targets_, int n_sequences_) +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Matrix DataSet. +The standard dataset, with data fully loaded in memory. +Usefull for large databases. + +

+
+ + + +
o MatDataSet(const char* filename, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Create a new dataset from the file filename. If the file contains only one sequence, set one_file_is_one_sequence +to true. If there is several sequences, and you want only to load the first n ones, set max_load to n (else max_load +should be a negative number). If binary_mode is true, the IOBin format will be used, else it will be the IOAscii format. + +

Input and target sequence will have the same number of frames. For each frame given by the dataset, the first n_inputs_ +real are for the inputs and then the next n_targets_ real are for the targets. (n_inputs_ is the input frame size and +n_targets_ is the target frame size). +

+ + +

o MatDataSet(char** filenames, int n_files_, int n_inputs_, int n_targets_, bool one_file_is_one_sequence=false, int max_load=-1, bool binary_mode=false) +
Same as the previous constructor, but for several files. If one_file_is_one_sequence is true, each files will be considered as they +had only one sequence. +

+ + +

o MatDataSet(char** input_filenames, char** target_filenames, int n_files_, int max_load=-1, bool binary_mode=false) +
Here the inputs and the targets are in separated files. +Input and target frame sizes are therefore auto-detected. +One file must correspond to one sequence. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
IOAscii +
IOBin +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MeanVarNorm.html b/torch3/manual/MeanVarNorm.html new file mode 100644 index 0000000..1cb90d7 --- /dev/null +++ b/torch3/manual/MeanVarNorm.html @@ -0,0 +1,176 @@ + + + + + class MeanVarNorm + + + + +

class MeanVarNorm

In the constructor, it computes the mean and the standard deviation over all the frames in the given DataSet (by default, only for inputs).
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_inputs +
Input frame size +
+[more]int n_targets +
Target frame size +
+[more]real* inputs_mean +
Inputs means array +
+[more]real* targets_mean +
Targets means array +
+[more]real* inputs_stdv +
Inputs standard deviations array +
+[more]real* targets_stdv +
Targets standard deviations array +

+ +

+

Public Methods

+[more] MeanVarNorm(DataSet* data, bool norm_inputs=true, bool norm_targets=false) +
+[more]virtual void loadXFile(XFile* file) +
Load means and standard deviations +
+[more]virtual void saveXFile(XFile* file) +
Save means and standard deviations +

+ +
+

Inherited from PreProcessing:

+
+

+

Public Methods

+ovirtual void preProcessInputs(Sequence* inputs) +
+ovirtual void preProcessTargets(Sequence* targets) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
In the constructor, it computes the mean and the standard deviation +over all the frames in the given DataSet (by default, only for inputs). +Then, when calling pre-processing methods, it normalizes each column +by this computed mean and stdv. (substracts the mean, then divides +by the standard deviation). + +

As a result, the mean of the full set of frames given by the concatenation +of all calls to setExample() will be 0, and the variance will be 1. + +

+
+ + + +
oint n_inputs +
Input frame size +

+ + +

oint n_targets +
Target frame size +

+ + +

oreal* inputs_mean +
Inputs means array +

+ + +

oreal* targets_mean +
Targets means array +

+ + +

oreal* inputs_stdv +
Inputs standard deviations array +

+ + +

oreal* targets_stdv +
Targets standard deviations array +

+ + +

o MeanVarNorm(DataSet* data, bool norm_inputs=true, bool norm_targets=false) +

+ + +

ovirtual void loadXFile(XFile* file) +
Load means and standard deviations +

+ + +

ovirtual void saveXFile(XFile* file) +
Save means and standard deviations +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Measurer.html b/torch3/manual/Measurer.html new file mode 100644 index 0000000..8eb377a --- /dev/null +++ b/torch3/manual/Measurer.html @@ -0,0 +1,185 @@ + + + + + class Measurer + + + + +

class Measurer

Used to measure what you want during training/testing.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]XFile* file +
The measurer save measures in this file +
+[more]DataSet* data +
The associated DataSet +
+[more]bool binary_mode +
Is the measurer in binary mode ? +

+ +

+

Public Methods

+[more] Measurer(DataSet* data_, XFile* file_) +
Measurer with the associated DataSet data_, and put results in the file file_ +
+[more]virtual void measureExample() +
Measure something for the current example. +
+[more]virtual void measureIteration() +
Measure something after the current iteration. +
+[more]virtual void measureEnd() +
Measure something at the end of the training/testing phase +
+[more]virtual void reset() +
Reset the measurer. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Used to measure what you want during training/testing. +Usually, trainers call measurers. +The DataSet associated to the measurer allow us +to know when the measurer should be called. +(if the DataSet is the train dataset, the +measurer will be called during the train phase...) + +

Options: + +
+"binary mode" bool binary mode for output [false] +
+ +

+
+ + + +
oXFile* file +
The measurer save measures in this file +

+ + +

oDataSet* data +
The associated DataSet +

+ + +

obool binary_mode +
Is the measurer in binary mode ? +

+ + +

o Measurer(DataSet* data_, XFile* file_) +
Measurer with the associated DataSet data_, +and put results in the file file_ +

+ + +

ovirtual void measureExample() +
Measure something for the current example. +(This example has been selected in data +by the trainer) +

+ + +

ovirtual void measureIteration() +
Measure something after the current iteration. +(After the call of measureExample() for each +example of data) +

+ + +

ovirtual void measureEnd() +
Measure something at the end of the training/testing phase +

+ + +

ovirtual void reset() +
Reset the measurer. (By default, do nothing). +

+
+
Direct child classes: +
WordSegMeasurer
+TimeMeasurer
+SaturationMeasurer
+OutputMeasurer
+NLLMeasurer
+MSEMeasurer
+FrameSegMeasurer
+EditDistanceMeasurer
+ClassNLLMeasurer
+ClassMeasurer
+BoostingMeasurer
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MemoryDataSet.html b/torch3/manual/MemoryDataSet.html new file mode 100644 index 0000000..4b9ea80 --- /dev/null +++ b/torch3/manual/MemoryDataSet.html @@ -0,0 +1,193 @@ + + + + + class MemoryDataSet + + + + +

class MemoryDataSet

DataSet where data is fully loaded in memory.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Sequence** inputs_array +
Inputs array +
+[more]Sequence** targets_array +
Targets array +

+ +

+

Public Methods

+[more] MemoryDataSet() +
+[more]void init(IOSequence* io_inputs, IOSequence* io_outputs) +
May help you to initialize the DataSet if you're using IOSequence. +
+[more]void setInputs(Sequence** inputs_, int n_sequences_) +
Override current inputs array +
+[more]void setTargets(Sequence** targets_, int n_sequences_) +
Override current targets array +

+ +
+

Inherited from DataSet:

+
+

+

Public Fields

+oint* selected_examples +
+oint n_inputs +
+oint n_targets +
+oint real_current_example_index +
+oSequence* inputs +
+oSequence* targets +
+oint n_examples +
+oint n_real_examples +

+ +

+

Public Methods

+ovoid setExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void setRealExample(int t, bool set_inputs=true, bool set_targets=true) +
+ovirtual void pushSubset(int* subset_, int n_examples_) +
+ovirtual void popSubset() +
+ovirtual void pushExample() +
+ovirtual void popExample() +
+ovirtual void getNumberOfFrames(int t, int* n_input_frames, int* n_target_frames) +
+ovirtual void preProcess(PreProcessing* pre_processing) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
DataSet where data is fully loaded in memory. + +

Inputs and targets are put in two arrays: inputs_array and targets_array. +You can fill these fields by using the init() method (if you are using +IOSequence). But you could imagine a MemoryDataSet where you fill these fields +by hand (based on the init() method). +MatDataSet is a good example if you plan to do a new MemoryDataSet. + +

+
+ + + +
oSequence** inputs_array +
Inputs array +

+ + +

oSequence** targets_array +
Targets array +

+ + +

o MemoryDataSet() +

+ + +

ovoid init(IOSequence* io_inputs, IOSequence* io_outputs) +
May help you to initialize the DataSet if you're using IOSequence. +You should call this method in the constructor of your subsclasses. +Initialize n_examples, n_real_examples, n_inputs and n_targets. +inputs_array and targets_array filled with sequences given by the IOSequence classes. +

+ + +

ovoid setInputs(Sequence** inputs_, int n_sequences_) +
Override current inputs array +

+ + +

ovoid setTargets(Sequence** targets_, int n_sequences_) +
Override current targets array +

+
+
Direct child classes: +
MatDataSet
+HTKDataSet
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
MatDataSet +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MemoryXFile.html b/torch3/manual/MemoryXFile.html new file mode 100644 index 0000000..43d09e0 --- /dev/null +++ b/torch3/manual/MemoryXFile.html @@ -0,0 +1,214 @@ + + + + + class MemoryXFile + + + + +

class MemoryXFile

A file in the memory.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]MemoryXFileList* memory +
The memory +
+[more]int position +
The position in the memory +
+[more]int size +
The size of the memory +
+[more]int total_size +
The total size of the memory, including allocated buffer +
+[more]int buffer_size +
Minimal number of bytes that will be allocated when writing +

+ +

+

Public Methods

+[more] MemoryXFile(int buffer_format_size_=256) +
Create a read-write file from nothing +
+[more] MemoryXFile(MemoryXFileList* memory_, int size_=-1, int buffer_format_size_=256) +
Give a MemoryXFileList for the memory. +
+[more] MemoryXFile(void* memory_, int size_, int buffer_format_size_=256) +
Give a pointer for the memory. +
+[more]void concat() +
Concat all the memory in one node. +
+[more]virtual int scanf(const char* format, void* ptr) +
Warning: this method call the concat function, and therefore could take time if you do intensive read/write. +

+ +
+

Inherited from XFile:

+
+

+

Public Methods

+ovirtual int read(void* ptr, int block_size, int n_blocks) +
+ovirtual int write(void* ptr, int block_size, int n_blocks) +
+oint taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
+oint taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
+ovirtual int eof() +
+ovirtual int flush() +
+ovirtual int seek(long offset, int whence) +
+ovirtual long tell() +
+ovirtual void rewind() +
+ovirtual int printf(const char* format, ...) +
+ovirtual char* gets(char* dest, int size_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A file in the memory. +Note that the MemoryXFile is a read-write file! +When writing, data is buffered (to avoid reallocating blocks of small sizes!). + +

Options: + +
+"buffer size" int buffer size for writing [65536] +
+ +

+
+ + + +
oMemoryXFileList* memory +
The memory +

+ + +

oint position +
The position in the memory +

+ + +

oint size +
The size of the memory +

+ + +

oint total_size +
The total size of the memory, including allocated buffer +

+ + +

oint buffer_size +
Minimal number of bytes that will be allocated when writing +

+ + +

o MemoryXFile(int buffer_format_size_=256) +
Create a read-write file from nothing +

+ + +

o MemoryXFile(MemoryXFileList* memory_, int size_=-1, int buffer_format_size_=256) +
Give a MemoryXFileList for the memory. A new list is created, but the memory +in the nodes are not copied. +If the size that you want to be readable is less than the +sum of the n in the field of the MemoryXFileList, you can provide it in size_ +

+ + +

o MemoryXFile(void* memory_, int size_, int buffer_format_size_=256) +
Give a pointer for the memory. (No copy is done!) +

+ + +

ovoid concat() +
Concat all the memory in one node. Add a null character at the end. +This null character is useful for sscanf in the scanf method. +

+ + +

ovirtual int scanf(const char* format, void* ptr) +
Warning: this method call the concat function, +and therefore could take time if you do intensive read/write. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Mixer.html b/torch3/manual/Mixer.html new file mode 100644 index 0000000..cd5ca47 --- /dev/null +++ b/torch3/manual/Mixer.html @@ -0,0 +1,167 @@ + + + + + class Mixer + + + + +

class Mixer

Mixer useful for experts mixtures.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_experts +
Number of experts +

+ +

+

Public Methods

+[more] Mixer(int n_inputs_, int n_outputs_per_expert) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Mixer useful for experts mixtures. +Formally speaking, it computes: + + +

where +

    +
  • are in the table +of the first node of the inputs list, +when you call forward(). + +

  • are the inputs of the j-th expert. +Therefore, the inputs list has the structure +. +Only must be alone in one node. +
+ +

+
+ + + +
oint n_experts +
Number of experts +

+ + +

o Mixer(int n_inputs_, int n_outputs_per_expert) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MultiClassFormat.html b/torch3/manual/MultiClassFormat.html new file mode 100644 index 0000000..868ff63 --- /dev/null +++ b/torch3/manual/MultiClassFormat.html @@ -0,0 +1,139 @@ + + + + + class MultiClassFormat + + + + +

class MultiClassFormat

Define the multi class encoding format.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real* tabclasses +
Array of class labels +

+ +

+

Public Methods

+[more] MultiClassFormat(DataSet* data) +
Autodetect classes +
+[more] MultiClassFormat(int n_classes_, real* class_labels_=NULL) +
By default (if class_labels_ is not specified), class labels are 0, 1, +

+ +
+

Inherited from ClassFormat:

+
+

+

Public Fields

+oint n_classes +
+oreal** class_labels +

+ +

+

Public Methods

+ovirtual int getOutputSize() +
+ovirtual void fromOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual void toOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual int getClass(real* vector) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Define the multi class encoding format. +Each class is coded by a single number. + +

+
+ + + +
oreal* tabclasses +
Array of class labels +

+ + +

o MultiClassFormat(DataSet* data) +
Autodetect classes +

+ + +

o MultiClassFormat(int n_classes_, real* class_labels_=NULL) +
By default (if class_labels_ is not specified), class labels are 0, 1, +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/MultiCriterion.html b/torch3/manual/MultiCriterion.html new file mode 100644 index 0000000..882aedf --- /dev/null +++ b/torch3/manual/MultiCriterion.html @@ -0,0 +1,183 @@ + + + + + class MultiCriterion + + + + +

class MultiCriterion

MultiCriterion can be used to handle multiple criterions.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_criterions +
the number of criterions +
+[more]Criterion** criterions +
the criterions +
+[more]real* weights +
the relative weight of each criterion +

+ +

+

Public Methods

+[more] MultiCriterion(Criterion** criterions_, int n_criterions_, real* weights_ = NULL) +

+ +
+

Inherited from Criterion:

+
+

+

Public Fields

+oDataSet* data +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* data_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
MultiCriterion can be used to handle multiple criterions. + +

The MultiCriterion is a Criterion which is the weighted +sum of given criterions. (By default, the weights are equal to 1). + +

+
+ + + +
oint n_criterions +
the number of criterions +

+ + +

oCriterion** criterions +
the criterions +

+ + +

oreal* weights +
the relative weight of each criterion +

+ + +

o MultiCriterion(Criterion** criterions_, int n_criterions_, real* weights_ = NULL) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Multinomial.html b/torch3/manual/Multinomial.html new file mode 100644 index 0000000..c6a3844 --- /dev/null +++ b/torch3/manual/Multinomial.html @@ -0,0 +1,240 @@ + + + + + class Multinomial + + + + +

class Multinomial

This class can be used to model Multinomial Distributions.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_values +
number of values this multinomial can take +
+[more]real prior_weights +
the prior weight given to each value. +
+[more]bool equal_initialization +
if true then does equal initialization of the weights +
+[more]real* log_weights +
the pointers to the parameters +
+[more]real* dlog_weights +
the pointers to the d_parameters +
+[more]real* weights_acc +
accumulators for EM +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to model Multinomial Distributions. +They can be trained using either EM (with EMTrainer) or gradient descent +(with GMTrainer). + +

+
+ + + +
oint n_values +
number of values this multinomial can take +

+ + +

oreal prior_weights +
the prior weight given to each value. kind of smoother +

+ + +

obool equal_initialization +
if true then does equal initialization of the weights +

+ + +

oreal* log_weights +
the pointers to the parameters +

+ + +

oreal* dlog_weights +
the pointers to the d_parameters +

+ + +

oreal* weights_acc +
accumulators for EM +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/NLLCriterion.html b/torch3/manual/NLLCriterion.html new file mode 100644 index 0000000..e1fdf36 --- /dev/null +++ b/torch3/manual/NLLCriterion.html @@ -0,0 +1,158 @@ + + + + + class NLLCriterion + + + + +

class NLLCriterion

This criterion can be used to train Distribution object using the GMTrainer trainer.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] NLLCriterion() +

+ +
+

Inherited from Criterion:

+
+

+

Public Fields

+oDataSet* data +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* data_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This criterion can be used to train Distribution object using +the GMTrainer trainer. It then maximizes the log likelihood of the +data. + +

The forward method always return its input, which is the negative log +likelihood, while the backward method sets the gradient to -1. + +

+
+ + + +
o NLLCriterion() +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/NLLMeasurer.html b/torch3/manual/NLLMeasurer.html new file mode 100644 index 0000000..230af7a --- /dev/null +++ b/torch3/manual/NLLMeasurer.html @@ -0,0 +1,133 @@ + + + + + class NLLMeasurer + + + + +

class NLLMeasurer

This class measures the negative log likelihood.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Sequence* inputs +
contains a pointer to the negative log likelihood to measure +

+ +

+

Public Methods

+[more] NLLMeasurer(Sequence* inputs_, DataSet* data_, XFile* file_) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class measures the negative log likelihood. In fact, it supposes +that the input given is the positive log likelihood. It can +then normalized by the total number of frames and/or the number of total +of examples. + +

+
+ + + +
oSequence* inputs +
contains a pointer to the negative log likelihood to measure +

+ + +

o NLLMeasurer(Sequence* inputs_, DataSet* data_, XFile* file_) +

+ +
This class has no child classes.
+ +
Author:
Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/NPTrainer.html b/torch3/manual/NPTrainer.html new file mode 100644 index 0000000..f2bbd02 --- /dev/null +++ b/torch3/manual/NPTrainer.html @@ -0,0 +1,96 @@ + + + + + class NPTrainer + + + + +

class NPTrainer

Trainer for Non Parametric Machines.
+
+ +

Inheritance:

+ + + + + + + +

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Trainer for Non Parametric Machines. This trainer does nothing during +training! But it can be used to test Non Parametric models such as +KNN or ParzenDistributions or even select a correct hyper-parameter +using cross-validation. + +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/NavigatorButton.class b/torch3/manual/NavigatorButton.class new file mode 100644 index 0000000000000000000000000000000000000000..5fa134ee0f22ae5659bc0091d4cc98b3e6a0532a GIT binary patch literal 1816 zcma)7S#ujj5dOxJHIlr(EguO9h9t&b+fld=C4tzn6A=-+FmbSpYrI~`YgW5rHIi-4 z-$D2RyyS%xl7Uq5NUHcz6g{)6i}C{x>hAfbr|)h3{m&nNB8FxBki?B7wvzaWqrh>W zV}s)pjxRY}jxvYG;d4|tzTyZtsvI(n6z0ROx-Zk(Yb`5-w z+YE!VPIWf#NjoSC%VrpzUnm@ky2y$nnO*linPZq}VXp8>*)173UWwq?{K7WF_%P`iZr@g7ia}n61-1WX4!P5UyT&Wd{c0d95 zs7FSkY`ZdRt7p2cx6~=TsWb3=UIo5##!VQvXUpt^4+~KhM5W>qa7(jQDzbenbGy5t zkxnX)xbAq4yvdMWbw#y$ClHkbhT+cPs_Iz}vMD^xc6Ni!s=rnV?kV}?S!m9YYROSs!2aKxT#Q&7YAMcpY0=?5z{DSeM(-tudK zWv@FfCBSHu62ej$D4|lZy?x4dPiGh3^IbY66;pvQa4W1iNhMo`Sh5uOM+Lh`*9phl zr;#NCs_Iljr`q*}q#Y?-#|mG~gx|^;HKCZ>-%%^(p*EsxMC0EDlqXx9{5MMeXCa13G`PhdY2@n-wGmD3uqX5UCrA@5ujCwKO;dq7Wm0rJjIxq>2KhIx!k~v zxzxa%nTa=W-pnK#xNK&41J9YiV)_}z&8IMS#$xdi;}jDOOcQ*u1NTSpMS?Hs!+@!*H1Ptl%a6k2G#!7@!807-y(s88 z#7P3qMHa{U$e!86xh689#nzk8u@b$xhCcdlgU(>?FHDk?8RhqPT~V#~za| R#{{M@M4Akr679nW{{js3#=-yq literal 0 HcmV?d00001 diff --git a/torch3/manual/NullXFile.html b/torch3/manual/NullXFile.html new file mode 100644 index 0000000..c8ad0f7 --- /dev/null +++ b/torch3/manual/NullXFile.html @@ -0,0 +1,127 @@ + + + + + class NullXFile + + + + +

class NullXFile

NullXFile.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] NullXFile() +

+ +
+

Inherited from XFile:

+
+

+

Public Methods

+ovirtual int read(void* ptr, int block_size, int n_blocks) +
+ovirtual int write(void* ptr, int block_size, int n_blocks) +
+oint taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
+oint taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
+ovirtual int eof() +
+ovirtual int flush() +
+ovirtual int seek(long offset, int whence) +
+ovirtual long tell() +
+ovirtual void rewind() +
+ovirtual int printf(const char* format, ...) +
+ovirtual int scanf(const char* format, void* ptr) +
+ovirtual char* gets(char* dest, int size_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
NullXFile. A XFile which do nothing! +Equivalent to the "/dev/null" file on UNIX systems. + +

+
+ + + +
o NullXFile() +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Object.html b/torch3/manual/Object.html new file mode 100644 index 0000000..f5a6ec7 --- /dev/null +++ b/torch3/manual/Object.html @@ -0,0 +1,240 @@ + + + + + class Object + + + + +

class Object

Almost all classes in Torch should be a sub-class of this class.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Allocator* allocator +
Allocator associated to the Object +

+ +

+

Public Methods

+[more] Object() +
+[more]void addOption(const char* name, int size, void* ptr, const char* help="") +
Add the option name. +
+[more]void addIOption(const char* name, int* ptr, int init_value, const char* help="") +
Several wrappers of addOption() for Int, Real and Bool options. +
+[more]void addROption(const char* name, real* ptr, real init_value, const char* help="") +
+[more]void addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+[more]void addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+[more]void setOption(const char* name, void* ptr) +
Set the option name to the value contained at ptr +
+[more]void setIOption(const char* name, int option) +
Several wrappers of setOption() for Int, Real and Bool options. +
+[more]void setROption(const char* name, real option) +
+[more]void setBOption(const char* name, bool option) +
+[more]void setOOption(const char* name, Object* option) +
+[more]virtual void loadXFile(XFile* file) +
Load the object from a file pointer (not the options) +
+[more]virtual void saveXFile(XFile* file) +
Save the object to a file pointer (not the options) +
+[more]void load(const char* filename) +
Load the machine from a file name (not the options) +
+[more]void save(const char* filename) +
Save the machine to a file name (not the options) +
+[more]void* operator new(size_t size, Allocator* allocator_=NULL) +
Allocate the object using allocator_. +
+[more]void* operator new(size_t size, Allocator* allocator_, void* ptr_) +
Allocate the object using the memory given by ptr_. +
+[more]void operator delete(void* ptr) +
Delete an object +

+ +
+ + +
+

Documentation

+
Almost all classes in Torch should be a sub-class of this class. +It provides two interesting things: first a useful interface to +manage option, and second the "allocator trick". + +

Indeed, in Torch, a class which allocate memory should desallocate +this memory when it's destroyed. The idea is the following: in the +constructor of Object, an Allocator object is created. You can use +it in your subclasses to allocate memory. This memory will be destroyed +when the Object is destroyed. + +

"new" operator have been defined to be used with Allocator. + +

+
+ + + +
oAllocator* allocator +
Allocator associated to the Object +

+ + +

o Object() +

+ + +

ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
Add the option name. +This one has a pointer on ptr and has the size size. +You can provide an help in help. +(Note that if help is empty, its an empty string and not NULL). +If the option can be changed at any time, you can set +is_allowed_after_init to true. +

+ + +

ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
Several wrappers of addOption() for +Int, Real and Bool options. +Be carefull: there is no type checking. +

+ + +

ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +

+ + +

ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +

+ + +

ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +

+ + +

ovoid setOption(const char* name, void* ptr) +
Set the option name to the value contained at ptr +

+ + +

ovoid setIOption(const char* name, int option) +
Several wrappers of setOption() for +Int, Real and Bool options. +Be carefull: there is no type checking. +

+ + +

ovoid setROption(const char* name, real option) +

+ + +

ovoid setBOption(const char* name, bool option) +

+ + +

ovoid setOOption(const char* name, Object* option) +

+ + +

ovirtual void loadXFile(XFile* file) +
Load the object from a file pointer (not the options) +

+ + +

ovirtual void saveXFile(XFile* file) +
Save the object to a file pointer (not the options) +

+ + +

ovoid load(const char* filename) +
Load the machine from a file name (not the options) +

+ + +

ovoid save(const char* filename) +
Save the machine to a file name (not the options) +

+ + +

ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
Allocate the object using allocator_. The object will be +destroyed and freed when the allocator will be destroyed. +If no allocator is provided, the new will be similar than +the standard new. +

+ + +

ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
Allocate the object using the memory given by ptr_. +The object will be destroyed (but not freed!) when the +allocator will be destroyed. +

+ + +

ovoid operator delete(void* ptr) +
Delete an object +

+
+
Direct child classes: +
XFile
+WordSeg
+Vocabulary
+Vec
+Trainer
+Timer
+Stack
+Sequence
+QCCache
+PreProcessing
+PhoneInfo
+Perm
+Parameters
+Measurer
+Mat
+Machine
+LexiconInfo
+Kernel
+KFold
+IOSequenceArray
+IOSequence
+Grammar
+FrameSeg
+EditDistance
+DataSet
+CmdOption
+CmdLine
+ClassFormat
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
Allocator +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/OneHotClassFormat.html b/torch3/manual/OneHotClassFormat.html new file mode 100644 index 0000000..4dcbb37 --- /dev/null +++ b/torch3/manual/OneHotClassFormat.html @@ -0,0 +1,128 @@ + + + + + class OneHotClassFormat + + + + +

class OneHotClassFormat

Define the one hot class encoding format.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] OneHotClassFormat(DataSet* data) +
Autodetect number of classes. +
+[more] OneHotClassFormat(int n_targets) +
Specify the number of targets +

+ +
+

Inherited from ClassFormat:

+
+

+

Public Fields

+oint n_classes +
+oreal** class_labels +

+ +

+

Public Methods

+ovirtual int getOutputSize() +
+ovirtual void fromOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual void toOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual int getClass(real* vector) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Define the one hot class encoding format. + +

+
+ + + +
o OneHotClassFormat(DataSet* data) +
Autodetect number of classes. +(Equal to the frame size of the targets). +

+ + +

o OneHotClassFormat(int n_targets) +
Specify the number of targets +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/OutputMeasurer.html b/torch3/manual/OutputMeasurer.html new file mode 100644 index 0000000..1c3a59e --- /dev/null +++ b/torch3/manual/OutputMeasurer.html @@ -0,0 +1,150 @@ + + + + + class OutputMeasurer + + + + +

class OutputMeasurer

Compute the outputification error (in %) of the inputs with respect to the targets of data.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]SequenceList* sequences +
Sequences to output +
+[more]int total_frame_size +
Sum of frame size of all sequences +

+ +

+

Public Methods

+[more] OutputMeasurer(DataSet* data_, XFile* file_) +
+[more]void addSequence(Sequence* sequence) +
Adds a sequence which will be outputed +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Compute the outputification error (in %) +of the inputs with respect to the targets of data. + +

The format of the output is given with a OutputFormat. +It can print the confusion matrix if specified. + +

+
+ + + +
oSequenceList* sequences +
Sequences to output +

+ + +

oint total_frame_size +
Sum of frame size of all sequences +

+ + +

o OutputMeasurer(DataSet* data_, XFile* file_) +

+ + +

ovoid addSequence(Sequence* sequence) +
Adds a sequence which will be outputed +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Parameters.html b/torch3/manual/Parameters.html new file mode 100644 index 0000000..c9274bd --- /dev/null +++ b/torch3/manual/Parameters.html @@ -0,0 +1,203 @@ + + + + + class Parameters + + + + +

class Parameters

Parameters definition.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real** data +
Array of pointers to array of parameters. +
+[more]int n_data +
Size of data +
+[more]int* size +
size[i] is the size of data[i] +
+[more]int n_params +
Total number of parameters +

+ +

+

Public Methods

+[more] Parameters() +
No parameters ? +
+[more] Parameters(int n_params_) +
Create one entry in data with the given size +
+[more]void addParameters(real* params, int n_params_, bool do_copy=false) +
Add an entry in data. +
+[more]void add(Parameters* params, bool do_copy=false) +
Add all entries given by params in data. +
+[more]void copy(Parameters* from) +
Copy the given parameters. +
+[more]void copyFrom(real* vec) +
Copy a real vector in the parameters. +
+[more]void copyTo(real* vec) +
Copy the full parameters in a real vector. +
+[more]virtual void saveXFile(XFile* file) +
Save all the parameters +
+[more]virtual void loadXFile(XFile* file) +
Load all the parameters +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Parameters definition. +Parameters are a bench of real arrays. + +

+
+ + + +
oreal** data +
Array of pointers to array of parameters. +The size of this array is given by n_data. +The size of data[i] is given by size[i] +

+ + +

oint n_data +
Size of data +

+ + +

oint* size +
size[i] is the size of data[i] +

+ + +

oint n_params +
Total number of parameters +

+ + +

o Parameters() +
No parameters ? +

+ + +

o Parameters(int n_params_) +
Create one entry in data with the given size +

+ + +

ovoid addParameters(real* params, int n_params_, bool do_copy=false) +
Add an entry in data. +If do_copy is true, copy the parameters. +Else, just copy the pointer. +

+ + +

ovoid add(Parameters* params, bool do_copy=false) +
Add all entries given by params in data. +If do_copy is true, copy the parameters, else just copy the pointers. +

+ + +

ovoid copy(Parameters* from) +
Copy the given parameters. +The given parameters don't need to have the same structure. +But it must have the same total length. +

+ + +

ovoid copyFrom(real* vec) +
Copy a real vector in the parameters. +The parameters must have the good size! +

+ + +

ovoid copyTo(real* vec) +
Copy the full parameters in a real vector. +The parameters must have the good size! +

+ + +

ovirtual void saveXFile(XFile* file) +
Save all the parameters +

+ + +

ovirtual void loadXFile(XFile* file) +
Load all the parameters +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ParzenDistribution.html b/torch3/manual/ParzenDistribution.html new file mode 100644 index 0000000..646a3c6 --- /dev/null +++ b/torch3/manual/ParzenDistribution.html @@ -0,0 +1,236 @@ + + + + + class ParzenDistribution + + + + +

class ParzenDistribution

This class can be used to model a Parzen density estimator with a Gaussian kernel:
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real var +
the variance used +
+[more]DataSet* data +
the dataset +
+[more]int* train_examples_index +
the indices of the training examples +
+[more]real sum_log_var_plus_n_obs_log_2_pi +
in order to faster the computation, we can do some "pre-computation" pre-computed sum_log_var + n_obs * log_2_pi +
+[more]real minus_half_over_var +
pre-computed -05 / var +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to model a Parzen density estimator with +a Gaussian kernel: + +

+ +

where the sum is done on the whole training set. + +

+
+ + + +
oreal var +
the variance used +

+ + +

oDataSet* data +
the dataset +

+ + +

oint* train_examples_index +
the indices of the training examples +

+ + +

oreal sum_log_var_plus_n_obs_log_2_pi +
in order to faster the computation, we can do some "pre-computation" +pre-computed sum_log_var + n_obs * log_2_pi +

+ + +

oreal minus_half_over_var +
pre-computed -05 / var +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/ParzenMachine.html b/torch3/manual/ParzenMachine.html new file mode 100644 index 0000000..84f7086 --- /dev/null +++ b/torch3/manual/ParzenMachine.html @@ -0,0 +1,179 @@ + + + + + class ParzenMachine + + + + +

class ParzenMachine

This machine implements the Parzen Window estimator.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real var +
the variance used +
+[more]DataSet* data +
The dataset that contains the training set +
+[more]int* real_examples +
the indices of the training examples +
+[more]real denominator +
keep the denominator +
+[more]int n_outputs +
the size of the output vector +
+[more]int n_inputs +
the size of the input vector +

+ +

+

Public Methods

+[more] ParzenMachine(int n_inputs_, int n_outputs_, real var_) +
+[more]virtual void setVar(real var_) +
change the value of var +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This machine implements the Parzen Window estimator. +Given a dataset (in the constructor), the forward method returns +for a given input the average of the outputs of the training set +weighted by a Gaussian kernel distance: + +

+ +

The only parameter var is given in the constructor. + +

+
+ + + +
oreal var +
the variance used +

+ + +

oDataSet* data +
The dataset that contains the training set +

+ + +

oint* real_examples +
the indices of the training examples +

+ + +

oreal denominator +
keep the denominator +

+ + +

oint n_outputs +
the size of the output vector +

+ + +

oint n_inputs +
the size of the input vector +

+ + +

o ParzenMachine(int n_inputs_, int n_outputs_, real var_) +

+ + +

ovirtual void setVar(real var_) +
change the value of var +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Perm.html b/torch3/manual/Perm.html new file mode 100644 index 0000000..c28a9a0 --- /dev/null +++ b/torch3/manual/Perm.html @@ -0,0 +1,125 @@ + + + + + class Perm + + + + +

class Perm

Permutation object.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n +
Size of the permutation +
+[more]int* ptr +
Data of the permutation +

+ +

+

Public Methods

+[more] Perm(int n_dim) +
Create a new permutation +
+[more]void copy(Perm* perm) +
Copy the permutation perm +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Permutation object. + +

+
+ + + +
oint n +
Size of the permutation +

+ + +

oint* ptr +
Data of the permutation +

+ + +

o Perm(int n_dim) +
Create a new permutation +

+ + +

ovoid copy(Perm* perm) +
Copy the permutation perm +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/PhoneInfo.html b/torch3/manual/PhoneInfo.html new file mode 100644 index 0000000..c0382b5 --- /dev/null +++ b/torch3/manual/PhoneInfo.html @@ -0,0 +1,185 @@ + + + + + class PhoneInfo + + + + +

class PhoneInfo

This class contains the names of the phonemes that make up the words in the lexicon.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] PhoneInfo() +
Creates an empty PhoneInfo instance +
+[more]char* getPhone( int index ) +
Returns a pointer to the phoneme name at position "index" in the list +

+ +

+

Public Members

+[more] Reads the phone information from 'phones_fname' file. +
+[more] Looks at the first line of the file. +
+[more] If it is "PHONE" then the file is assumed to be in Noway phone models format. +
+[more] If it is "~o" then the file is assumed to be in HTK model definition format +
+[more] Otherwise the file is assumed to contain just a straight list of phone names +
+[more] If the sil_name and pause_name params are set, then the indices of the +
+[more] Adds a phoneme to the end of the list of phonemes +
+[more] is_sil and is_pause indicate if the phoneme is one of the special phonemes +
+[more] Does a linear search through the list and returns the index of the +
+[more] phoneme name supplied as a parameter +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
+This class contains the names of the phonemes that make up +the words in the lexicon. An empty instance can be created, +and then phones added manually using the addPhone method, +or a filename can be specified containing phone information. +The list of phone names is then extracted automatically +from the file. + +

+
+ + + +
o PhoneInfo() +
Creates an empty PhoneInfo instance +

+ + +

o Reads the phone information from 'phones_fname' file. +
Reads the phone information from 'phones_fname' file. +

+ + +

o Looks at the first line of the file. +
Looks at the first line of the file. +

+ + +

o If it is "PHONE" then the file is assumed to be in Noway phone models format. +
If it is "PHONE" then the file is assumed to be in Noway phone models format. +

+ + +

o If it is "~o" then the file is assumed to be in HTK model definition format +
If it is "~o" then the file is assumed to be in HTK model definition format +

+ + +

o Otherwise the file is assumed to contain just a straight list of phone names +
Otherwise the file is assumed to contain just a straight list of phone names +

+ + +

o If the sil_name and pause_name params are set, then the indices of the +
If the sil_name and pause_name params are set, then the indices of the +

+ + +

o Adds a phoneme to the end of the list of phonemes +
Adds a phoneme to the end of the list of phonemes +

+ + +

o is_sil and is_pause indicate if the phoneme is one of the special phonemes +
is_sil and is_pause indicate if the phoneme is one of the special phonemes +

+ + +

ochar* getPhone( int index ) +
Returns a pointer to the phoneme name at position "index" in the list +

+ + +

o Does a linear search through the list and returns the index of the +
Does a linear search through the list and returns the index of the +

+ + +

o phoneme name supplied as a parameter +
phoneme name supplied as a parameter +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/PhoneModels.html b/torch3/manual/PhoneModels.html new file mode 100644 index 0000000..5898616 --- /dev/null +++ b/torch3/manual/PhoneModels.html @@ -0,0 +1,22 @@ + + + + + class PhoneModels + + + + +

class PhoneModels

+ +
+

Documentation

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/PipeXFile.html b/torch3/manual/PipeXFile.html new file mode 100644 index 0000000..e92c873 --- /dev/null +++ b/torch3/manual/PipeXFile.html @@ -0,0 +1,146 @@ + + + + + class PipeXFile + + + + +

class PipeXFile

A file in a pipe.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] PipeXFile(const char* command, const char* open_flags) +
Execute command with the flags open_flags +

+ +
+

Inherited from DiskXFile:

+
+

+

Public Methods

+ostatic bool isLittleEndianProcessor() +
+ostatic bool isBigEndianProcessor() +
+ostatic bool isNativeMode() +
+ostatic void setNativeMode() +
+ostatic void setLittleEndianMode() +
+ostatic void setBigEndianMode() +

+ +
+

Inherited from XFile:

+
+

+

Public Methods

+ovirtual int read(void* ptr, int block_size, int n_blocks) +
+ovirtual int write(void* ptr, int block_size, int n_blocks) +
+oint taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
+oint taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
+ovirtual int eof() +
+ovirtual int flush() +
+ovirtual int seek(long offset, int whence) +
+ovirtual long tell() +
+ovirtual void rewind() +
+ovirtual int printf(const char* format, ...) +
+ovirtual int scanf(const char* format, void* ptr) +
+ovirtual char* gets(char* dest, int size_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
A file in a pipe. + +

+
+ + + +
o PipeXFile(const char* command, const char* open_flags) +
Execute command with the flags open_flags +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/PolynomialKernel.html b/torch3/manual/PolynomialKernel.html new file mode 100644 index 0000000..1df2851 --- /dev/null +++ b/torch3/manual/PolynomialKernel.html @@ -0,0 +1,104 @@ + + + + + class PolynomialKernel + + + + +

class PolynomialKernel

Polynomial Kernel .
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] PolynomialKernel(int degree, real s_=1., real r_=1.) +

+ +
+

Inherited from Kernel:

+
+

+

Public Methods

+ovirtual real eval(Sequence* x, Sequence* y) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Polynomial Kernel . + +

+
+ + + +
o PolynomialKernel(int degree, real s_=1., real r_=1.) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/PreProcessing.html b/torch3/manual/PreProcessing.html new file mode 100644 index 0000000..6042edb --- /dev/null +++ b/torch3/manual/PreProcessing.html @@ -0,0 +1,117 @@ + + + + + class PreProcessing + + + + +

class PreProcessing

This class is able to do pre-processing on examples in a DataSet.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] PreProcessing() +
+[more]virtual void preProcessInputs(Sequence* inputs) = 0 +
Given an input sequence, do the pre-processing +
+[more]virtual void preProcessTargets(Sequence* targets) = 0 +
Given an target sequence, do the pre-processing +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class is able to do pre-processing on examples +in a DataSet. Pre-processing doesn't modify the +structure of sequences, but only the contents. + +

+
+ + + +
o PreProcessing() +

+ + +

ovirtual void preProcessInputs(Sequence* inputs) = 0 +
Given an input sequence, do the pre-processing +

+ + +

ovirtual void preProcessTargets(Sequence* targets) = 0 +
Given an target sequence, do the pre-processing +

+
+
Direct child classes: +
MeanVarNorm
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
DataSet +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/QCCache.html b/torch3/manual/QCCache.html new file mode 100644 index 0000000..607733b --- /dev/null +++ b/torch3/manual/QCCache.html @@ -0,0 +1,147 @@ + + + + + class QCCache + + + + +

class QCCache

"Cache" used by the Quadratic Constrained Trainer (QCTrainer).
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] QCCache() +
+[more]virtual real* adressCache(int index) = 0 +
Returns the adress of the row/column index for the Q matrix +
+[more]virtual void allocate() = 0 +
Allocate the cache +
+[more]virtual void clear() = 0 +
Erase the cache (but don't destroy it) +
+[more]virtual void destroy() = 0 +
Destroy the cache +
+[more]virtual void setActiveVariables(int* active_var_, int n_active_var_) = 0 +
Set the active variables to be those contained in active_var. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
"Cache" used by the Quadratic Constrained Trainer (QCTrainer). +This class provides the Q (symetric) matrix of the +quadratic problem. + +

+
+ + + +
o QCCache() +

+ + +

ovirtual real* adressCache(int index) = 0 +
Returns the adress of the row/column index for the Q matrix +

+ + +

ovirtual void allocate() = 0 +
Allocate the cache +

+ + +

ovirtual void clear() = 0 +
Erase the cache (but don't destroy it) +

+ + +

ovirtual void destroy() = 0 +
Destroy the cache +

+ + +

ovirtual void setActiveVariables(int* active_var_, int n_active_var_) = 0 +
Set the active variables to be those contained in active_var. +The number of active variable is given by n_active_var_. + +

(It's usefull for some problems) + +

+

See Also:
QCMachine +
QCTrainer

+
+
Direct child classes: +
SVMCache
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
QCTrainer

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/QCMachine.html b/torch3/manual/QCMachine.html new file mode 100644 index 0000000..65fbdb9 --- /dev/null +++ b/torch3/manual/QCMachine.html @@ -0,0 +1,203 @@ + + + + + class QCMachine + + + + +

class QCMachine

"Quadratic Constrained Machine".
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real* Cup +
+[more]real* Cdown +
+[more]real bound_eps +
+[more]int n_alpha +
+[more]real* alpha +
+[more]real* grad +
+[more]real* y +
+[more]QCCache* cache +

+ +

+

Public Methods

+[more] QCMachine() +
+[more]virtual void checkSupportVectors() = 0 +
Function called by QCTrainer after the optimization. +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
"Quadratic Constrained Machine". +It's a machine with alpha parameters which +are the minimum of a constrained quadratic problem. + +

The problem: + +

minimize + +

with the following constraints: +

    +
  • +
  • +
+ +

where , , are given by the user +and must be . + +

The number of alpha variable is determined here by l. +(Therefore, it determines the size of de Cup, Cdown et y...) + +

Note: if is closed to [ou ] with +the accuracy "eps bounds", is considered +to be equal to [ou ]. + +

Options: + +
+"eps bounds" real bound accuracy: [1E-4 in float, 1E-12 in double] +
+ +

+
+ + + +
oreal* Cup +

+ + +

oreal* Cdown +

+ + +

oreal bound_eps +

+ + +

oint n_alpha +

+ + +

oreal* alpha +

+ + +

oreal* grad +

+ + +

oreal* y +

+ + +

oQCCache* cache +

+ + +

o QCMachine() +

+ + +

ovirtual void checkSupportVectors() = 0 +
Function called by QCTrainer after the optimization. + +
See Also:
QCTrainer

+
+
Direct child classes: +
SVM
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/QCTrainer.html b/torch3/manual/QCTrainer.html new file mode 100644 index 0000000..9511125 --- /dev/null +++ b/torch3/manual/QCTrainer.html @@ -0,0 +1,141 @@ + + + + + class QCTrainer + + + + +

class QCTrainer

Train a QCMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] QCTrainer(QCMachine* qcmachine_) +
+[more]void train(DataSet* data, MeasurerList* measurers) +
Train it. +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Train a QCMachine. +With the conventions of QCMachine.h, +Q is given by the class QCCache (in cache) + +

Options: + +
+"unshrink" bool unshrink or not unshrink [false]
+"max unshrink" int maximal number of unshrinking [1]
+"iter shrink" int minimal number of iterations to shrink [100]
+"eps shrink" real shrinking accuracy [1E-4 (f) 1E-9 (d)]
+"end accuracy" real end accuracy [0.01]
+"iter message" int number of iterations between messages [1000] +
+ +

+Note: "iter shrink" must be carefully chosen. +Read http://www.ai.mit.edu/projects/jmlr/papers/volume1/collobert01a/collobert01a.ps.gz +for more details. + +

+
+ + + +
o QCTrainer(QCMachine* qcmachine_) +

+ + +

ovoid train(DataSet* data, MeasurerList* measurers) +
Train it. +Before calling this function, grad in qcmachine +must contain the gradient of QP(alpha) with respect +to alpha = 0. + +

( = , with the conventions of QCMachine.h) + +

Moreover alpha in qcmachine has to be zero. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
QCCache +
QCMachine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Random.html b/torch3/manual/Random.html new file mode 100644 index 0000000..2197f45 --- /dev/null +++ b/torch3/manual/Random.html @@ -0,0 +1,165 @@ + + + + + class Random + + + + +

class Random

Random class which contains several static random methods.
+
+ +
+

+

Public Methods

+[more]static void seed() +
Initializes the random number generator with the computer clock +
+[more]static void manualSeed(unsigned long the_seed_) +
Initializes the random number generator with the given long "the_seed_" +
+[more]static unsigned long getInitialSeed() +
Returns the starting seed used +
+[more]static unsigned long random() +
Generates a uniform 32 bits integer +
+[more]static real uniform() +
Generates a uniform random number on [0,1[ +
+[more]static void getShuffledIndices(int* indices, int n_indices) +
Returns in indices n_indices shuffled. +
+[more]static void shuffle(void* tabular, int size_elem, int n_elems) +
Shuffles tabular, which contains n_elems of size size_elem +
+[more]static real boundedUniform(real a, real b) +
Generates a uniform random number on [a,b[ (b>a) +
+[more]static real normal(real mean=0, real stdv=1) +
Generates a random number from a normal distribution. +
+[more]static real exponential(real lambda) +
Generates a random number from an exponential distribution. +
+[more]static real cauchy(real median=0, real sigma=1) +
Returns a random number from a Cauchy distribution. +
+[more]static real logNormal(real mean, real stdv) +
Generates a random number from a log-normal distribution. +
+[more]static int geometric(real p) +
Generates a random number from a geometric distribution. +
+[more]static bool bernouilli(real p=0.5) +
Returns true with probability and false with probability (p > 0) +

+ +
+ + +
+

Documentation

+
Random class which contains several static random methods. + +

These methods are based on a uniform random generator, +named "Mersenne Twister", available at: +http://www.math.keio.ac.jp/matumoto/emt.html. +Copyright Makoto Matsumoto and Takuji Nishimura. +(Have a look inside the implementation file for details). + +

The random generator can be initialized with the manualSeed() method. +Otherwise, it will be automatically initialized with a seed based +on the current computer clock. + +

+
+ + + +
ostatic void seed() +
Initializes the random number generator with the computer clock +

+ + +

ostatic void manualSeed(unsigned long the_seed_) +
Initializes the random number generator with the given long "the_seed_" +

+ + +

ostatic unsigned long getInitialSeed() +
Returns the starting seed used +

+ + +

ostatic unsigned long random() +
Generates a uniform 32 bits integer +

+ + +

ostatic real uniform() +
Generates a uniform random number on [0,1[ +

+ + +

ostatic void getShuffledIndices(int* indices, int n_indices) +
Returns in indices n_indices shuffled. (between 0 and n_indices-1). +

+ + +

ostatic void shuffle(void* tabular, int size_elem, int n_elems) +
Shuffles tabular, which contains n_elems of size size_elem +

+ + +

ostatic real boundedUniform(real a, real b) +
Generates a uniform random number on [a,b[ (b>a) +

+ + +

ostatic real normal(real mean=0, real stdv=1) +
Generates a random number from a normal distribution. +(With mean mean and standard deviation stdv >= 0). +

+ + +

ostatic real exponential(real lambda) +
Generates a random number from an exponential distribution. +The density is , where +lambda is a positive number. +

+ + +

ostatic real cauchy(real median=0, real sigma=1) +
Returns a random number from a Cauchy distribution. +The Cauchy density is +

+ + +

ostatic real logNormal(real mean, real stdv) +
Generates a random number from a log-normal distribution. +(mean > 0 is the mean of the log-normal distribution +and stdv is its standard deviation). +

+ + +

ostatic int geometric(real p) +
Generates a random number from a geometric distribution. +It returns an integer i, where . +p must satisfy . +

+ + +

ostatic bool bernouilli(real p=0.5) +
Returns true with probability and false with probability (p > 0) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/RealCmdOption.html b/torch3/manual/RealCmdOption.html new file mode 100644 index 0000000..5e5662f --- /dev/null +++ b/torch3/manual/RealCmdOption.html @@ -0,0 +1,128 @@ + + + + + class RealCmdOption + + + + +

class RealCmdOption

This class defines a real command-line option.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] RealCmdOption(const char* name_, real* ptr_, real init_value_, const char* help_="", bool save_=false) +

+ +
+

Inherited from CmdOption:

+
+

+

Public Fields

+ochar* name +
+ochar* type_name +
+ochar* help +
+obool save +
+obool is_setted +

+ +

+

Public Methods

+ovirtual void initValue() +
+ovirtual void printValue(XFile* file_) +
+ovirtual void read(int* argc_, char*** argv_) +
+obool isOption(bool set_=false) +
+obool isArgument(bool set_=false) +
+obool isText(bool set_=false) +
+obool isMasterSwitch(bool set_=false) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class defines a real command-line option. + +

+
+ + + +
o RealCmdOption(const char* name_, real* ptr_, real init_value_, const char* help_="", bool save_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/RoutinesfordeterminingHessenbergfactorisations..html b/torch3/manual/RoutinesfordeterminingHessenbergfactorisations..html new file mode 100644 index 0000000..d69b0e1 --- /dev/null +++ b/torch3/manual/RoutinesfordeterminingHessenbergfactorisations..html @@ -0,0 +1,45 @@ + + + + + Routines for determining Hessenberg factorisations. + + + + +

Routines for determining Hessenberg factorisations.

+
+

+
+void mxHFactor(Mat* mat, Vec* diag, Vec* beta) +
Compute Hessenberg factorisation in compact form. +
+void mxMakeHQ(Mat* h_mat, Vec* diag, Vec* beta, Mat* q_out) +
Construct the Hessenberg orthogonalising matrix Q. +
+void mxMakeH(Mat* h_mat, Mat* h_out) +
Construct actual Hessenberg matrix +

+ + + +
+

Documentation

+
+Routines for determining Hessenberg factorisations. + +

Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Routinesforsymmetriceigenvalueproblems..html b/torch3/manual/Routinesforsymmetriceigenvalueproblems..html new file mode 100644 index 0000000..317f8f1 --- /dev/null +++ b/torch3/manual/Routinesforsymmetriceigenvalueproblems..html @@ -0,0 +1,42 @@ + + + + + Routines for symmetric eigenvalue problems. + + + + +

Routines for symmetric eigenvalue problems.

+
+

+
+void mxTriEig(Vec* a, Vec* b, Mat* mat_q) +
Finds eigenvalues of symmetric tridiagonal matrices. +
+void mxSymEig(Mat* mat_a, Mat* mat_q, Vec* out) +
Computes eigenvalues of a dense symmetric matrix. +

+ + + +
+

Documentation

+
+Routines for symmetric eigenvalue problems. + +

Based on the "Meschach Library", available at the +anonymous ftp site thrain.anu.edu.au in the directory +pub/meschach. + +

+
+
+
Author:
David E. Stewart (david.stewart@anu.edu.au) +Zbigniew Leyk (zbigniew.leyk@anu.edu.au) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVM.html b/torch3/manual/SVM.html new file mode 100644 index 0000000..dd2c5c1 --- /dev/null +++ b/torch3/manual/SVM.html @@ -0,0 +1,242 @@ + + + + + class SVM + + + + +

class SVM

Support Vector Machine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Allocator* sv_allocator +
To allocate all stuff related to support vectors +
+[more]IOSequenceArray* io_sequence_array +
Give the sequence-format +
+[more]DataSet* data +
The dataset associated to the SVM +
+[more]Kernel* kernel +
The kernel associated to the SVM +
+[more]real b +
+[more]int* support_vectors +
The support vectors +
+[more]real* sv_alpha +
sv_alpha[i] is the weight of the SV i +
+[more]Sequence** sv_sequences +
SV sequences +
+[more]int n_support_vectors +
The number of support vectors +
+[more]int n_support_vectors_bound +
The number of support vectors which are at the bound "C" +

+ +

+

Public Methods

+[more] SVM(Kernel* kernel_, IOSequenceArray* io_sequence_array_=NULL) +
+[more]bool bCompute() +
Computes the b +

+ +
+

Inherited from QCMachine:

+
+

+

Public Fields

+oreal* Cup +
+oreal* Cdown +
+oreal bound_eps +
+oint n_alpha +
+oreal* alpha +
+oreal* grad +
+oreal* y +
+oQCCache* cache +

+ +

+

Public Methods

+ovirtual void checkSupportVectors() +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Support Vector Machine. + +

The Q matrix of QCMachine is in this case +, where is a kernel +and is the i-th example of data/ + +

The goal is to looking for the alpha and b +which are the best in a SVM-sense. + +

The learning function is + + +

+
+ + + +
oAllocator* sv_allocator +
To allocate all stuff related to support vectors +

+ + +

oIOSequenceArray* io_sequence_array +
Give the sequence-format +

+ + +

oDataSet* data +
The dataset associated to the SVM +

+ + +

oKernel* kernel +
The kernel associated to the SVM +

+ + +

oreal b +

+ + +

oint* support_vectors +
The support vectors +

+ + +

oreal* sv_alpha +
sv_alpha[i] is the weight of the SV i +

+ + +

oSequence** sv_sequences +
SV sequences +

+ + +

oint n_support_vectors +
The number of support vectors +

+ + +

oint n_support_vectors_bound +
The number of support vectors which are at the bound "C" +

+ + +

o SVM(Kernel* kernel_, IOSequenceArray* io_sequence_array_=NULL) +

+ + +

obool bCompute() +
Computes the b +

+
+
Direct child classes: +
SVMRegression
+SVMClassification
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVMCache.html b/torch3/manual/SVMCache.html new file mode 100644 index 0000000..cea5718 --- /dev/null +++ b/torch3/manual/SVMCache.html @@ -0,0 +1,119 @@ + + + + + class SVMCache + + + + +

class SVMCache

QCCache implementation for SVMs.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SVMCache(int n_alpha_, Kernel* kernel_, real cache_size_in_megs_) +

+ +
+

Inherited from QCCache:

+
+

+

Public Methods

+ovirtual real* adressCache(int index) +
+ovirtual void allocate() +
+ovirtual void clear() +
+ovirtual void destroy() +
+ovirtual void setActiveVariables(int* active_var_, int n_active_var_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
QCCache implementation for SVMs. +Compute the Q matrix. + +

+
+ + + +
o SVMCache(int n_alpha_, Kernel* kernel_, real cache_size_in_megs_) +

+
+
Direct child classes: +
SVMCacheRegression
+SVMCacheClassification
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
SVM +
QCMachine +
QCTrainer +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVMCacheClassification.html b/torch3/manual/SVMCacheClassification.html new file mode 100644 index 0000000..2bd03c8 --- /dev/null +++ b/torch3/manual/SVMCacheClassification.html @@ -0,0 +1,115 @@ + + + + + class SVMCacheClassification + + + + +

class SVMCacheClassification

Cache for SVM classification.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SVMCacheClassification(DataSet* data_, Kernel* kernel_, real cache_size_in_megs_) +

+ +
+

Inherited from SVMCache:

+
+
+

Inherited from QCCache:

+
+

+

Public Methods

+ovirtual real* adressCache(int index) +
+ovirtual void allocate() +
+ovirtual void clear() +
+ovirtual void destroy() +
+ovirtual void setActiveVariables(int* active_var_, int n_active_var_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Cache for SVM classification. + +

+
+ + + +
o SVMCacheClassification(DataSet* data_, Kernel* kernel_, real cache_size_in_megs_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVMCacheRegression.html b/torch3/manual/SVMCacheRegression.html new file mode 100644 index 0000000..c231c7e --- /dev/null +++ b/torch3/manual/SVMCacheRegression.html @@ -0,0 +1,115 @@ + + + + + class SVMCacheRegression + + + + +

class SVMCacheRegression

Cache for SVM regression.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SVMCacheRegression(DataSet* data_, Kernel* kernel_, real cache_size_in_megs_) +

+ +
+

Inherited from SVMCache:

+
+
+

Inherited from QCCache:

+
+

+

Public Methods

+ovirtual real* adressCache(int index) +
+ovirtual void allocate() +
+ovirtual void clear() +
+ovirtual void destroy() +
+ovirtual void setActiveVariables(int* active_var_, int n_active_var_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Cache for SVM regression. + +

+
+ + + +
o SVMCacheRegression(DataSet* data_, Kernel* kernel_, real cache_size_in_megs_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVMClassification.html b/torch3/manual/SVMClassification.html new file mode 100644 index 0000000..ce0ee9a --- /dev/null +++ b/torch3/manual/SVMClassification.html @@ -0,0 +1,192 @@ + + + + + class SVMClassification + + + + +

class SVMClassification

SVM in classification.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SVMClassification(Kernel* kernel_, real* C_=NULL, IOSequenceArray* io_sequence_array_=NULL) +

+ +
+

Inherited from SVM:

+
+

+

Public Fields

+oAllocator* sv_allocator +
+oIOSequenceArray* io_sequence_array +
+oDataSet* data +
+oKernel* kernel +
+oreal b +
+oint* support_vectors +
+oreal* sv_alpha +
+oSequence** sv_sequences +
+oint n_support_vectors +
+oint n_support_vectors_bound +

+ +

+

Public Methods

+obool bCompute() +

+ +
+

Inherited from QCMachine:

+
+

+

Public Fields

+oreal* Cup +
+oreal* Cdown +
+oreal bound_eps +
+oint n_alpha +
+oreal* alpha +
+oreal* grad +
+oreal* y +
+oQCCache* cache +

+ +

+

Public Methods

+ovirtual void checkSupportVectors() +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
SVM in classification. + +

Try to find the hyperplane +as + minimize + +

(where if , else ) + +

(in fact, we use a kernel instead of a dot product) + +

The coefficients are given in C_ when you +call the constructor. If this one is NULL, then +the value given by the "C" option is used for +all . +(The size of C_ must be data->n_real_examples) + +

Options: + +
+"C" real trade off between the weight decay and the error [100]
+"cache size" real cache size (in Mo) [50] +
+ +

+
+ + + +
o SVMClassification(Kernel* kernel_, real* C_=NULL, IOSequenceArray* io_sequence_array_=NULL) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SVMRegression.html b/torch3/manual/SVMRegression.html new file mode 100644 index 0000000..1d4c9ed --- /dev/null +++ b/torch3/manual/SVMRegression.html @@ -0,0 +1,198 @@ + + + + + class SVMRegression + + + + +

class SVMRegression

SVM in regression.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SVMRegression(Kernel* kernel_, real* C_=NULL, IOSequenceArray* io_sequence_array_=NULL) +

+ +
+

Inherited from SVM:

+
+

+

Public Fields

+oAllocator* sv_allocator +
+oIOSequenceArray* io_sequence_array +
+oDataSet* data +
+oKernel* kernel +
+oreal b +
+oint* support_vectors +
+oreal* sv_alpha +
+oSequence** sv_sequences +
+oint n_support_vectors +
+oint n_support_vectors_bound +

+ +

+

Public Methods

+obool bCompute() +

+ +
+

Inherited from QCMachine:

+
+

+

Public Fields

+oreal* Cup +
+oreal* Cdown +
+oreal bound_eps +
+oint n_alpha +
+oreal* alpha +
+oreal* grad +
+oreal* y +
+oQCCache* cache +

+ +

+

Public Methods

+ovirtual void checkSupportVectors() +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
SVM in regression. + +

Try to find the hyperplane f(x) = w.x+b +as + minimize + + +

(where if , else ) +(and is the number of training examples) +(the size of is here 2*) + +

("eps" is eps_regression in the code) + +

(in fact, we use a kernel kernel instead of +a dot product) + +

The coefficients are given by C_ when you +call the constructor. If this one is NULL, all +C_j will have the value given by the "C" option. +(The size of C_ must be 2*data->n_real_examples) + +

Options: + +
+"C" real trade off between the weight decay and the error [100]
+"eps regression" real size of the error tube [0.7]
+"cache size" real cache size (in Mo) [50] +
+ +

+
+ + + +
o SVMRegression(Kernel* kernel_, real* C_=NULL, IOSequenceArray* io_sequence_array_=NULL) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SaturationMeasurer.html b/torch3/manual/SaturationMeasurer.html new file mode 100644 index 0000000..cda9111 --- /dev/null +++ b/torch3/manual/SaturationMeasurer.html @@ -0,0 +1,125 @@ + + + + + class SaturationMeasurer + + + + +

class SaturationMeasurer

Measure the saturation of a GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SaturationMeasurer(GradientMachine* machine_, DataSet* data_, XFile* file_) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Measure the saturation of a GradientMachine. + +

Save in file (on two columns) +

    +
  • the absolute mean of the outputs of the machine. +
  • the absolute mean of the derivative of the parameters of the machine. +
+ +

+
+ + + +
o SaturationMeasurer(GradientMachine* machine_, DataSet* data_, XFile* file_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Sequence.html b/torch3/manual/Sequence.html new file mode 100644 index 0000000..c3a9d6c --- /dev/null +++ b/torch3/manual/Sequence.html @@ -0,0 +1,255 @@ + + + + + class Sequence + + + + +

class Sequence

Sequence definition.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_real_frames +
Real number of frames +
+[more]real** frames +
Array of usable frame pointers. +
+[more]int n_frames +
Number of visible frames +
+[more]int frame_size +
Frame size +

+ +

+

Public Methods

+[more] Sequence() +
Create an empty sequence +
+[more] Sequence(real** frames_, int n_frames_, int frame_size_) +
Create a sequences of n_frames_ frames with size frame_size_. +
+[more] Sequence(int n_frames_, int frame_size_) +
Create a sequence with n_frames_ standard frames of size frame_size +
+[more]void resize(int n_frames_, bool allocate_new_frames=true) +
Resize the sequence to n_frames_. +
+[more]void addFrame(real* frame, bool do_copy=false) +
Add a frame at the end of the Sequence. +
+[more]void add(Sequence* sequence, bool do_copy=false) +
Add a sequence at the end of the Sequence. +
+[more]void copy(Sequence* from) +
Copy the given sequence. +
+[more]void copyFrom(real* vec) +
Copy a real vector in the full sequence. +
+[more]void copyTo(real* vec) +
Copy the full sequence in a real vector. +
+[more]virtual int getSequenceSpace() +
Get the space needed to allocate one Sequence +
+[more]virtual int getFramesSpace() +
Get the space needed to allocate frames contained in the sequence +
+[more]virtual Sequence* clone(Allocator* allocator_=NULL, void* sequence_memory=NULL, void* frames_memory=NULL) +
Clone the sequence. +
+[more]virtual void saveXFile(XFile* file) +
Save the usable frames. +
+[more]virtual void loadXFile(XFile* file) +
Load the usable frames. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Sequence definition. +A sequence is a set of frames (that is, a vector) which have the same size. + +

+
+ + + +
oint n_real_frames +
Real number of frames +

+ + +

oreal** frames +
Array of usable frame pointers. +The actual size of this array is given by n_real_frames. +And the usable size is given by n_frames. +

+ + +

oint n_frames +
Number of visible frames +

+ + +

oint frame_size +
Frame size +

+ + +

o Sequence() +
Create an empty sequence +

+ + +

o Sequence(real** frames_, int n_frames_, int frame_size_) +
Create a sequences of n_frames_ frames with size frame_size_. +The frames are given by the frames_ array. +Nothing (except pointers!) will be copied. +

+ + +

o Sequence(int n_frames_, int frame_size_) +
Create a sequence with n_frames_ standard frames +of size frame_size +

+ + +

ovoid resize(int n_frames_, bool allocate_new_frames=true) +
Resize the sequence to n_frames_. Note that if n_frames_ is lower +than the previous one, the frames won't be deallocated, and can be retrieved +by another resize... +

+ + +

ovoid addFrame(real* frame, bool do_copy=false) +
Add a frame at the end of the Sequence. +If do_copy is true, copy the sequence. +Else, just copy the pointer. +

+ + +

ovoid add(Sequence* sequence, bool do_copy=false) +
Add a sequence at the end of the Sequence. +If do_copy is true, copy the frame contents. +Else, just copy the frame pointers. +

+ + +

ovoid copy(Sequence* from) +
Copy the given sequence. +The given sequence don't need to have the same structure. +But it must have the same total length. +

+ + +

ovoid copyFrom(real* vec) +
Copy a real vector in the full sequence. +The sequence must have the good size! +

+ + +

ovoid copyTo(real* vec) +
Copy the full sequence in a real vector. +The sequence must have the good size! +

+ + +

ovirtual int getSequenceSpace() +
Get the space needed to allocate one Sequence +

+ + +

ovirtual int getFramesSpace() +
Get the space needed to allocate frames contained in the sequence +

+ + +

ovirtual Sequence* clone(Allocator* allocator_=NULL, void* sequence_memory=NULL, void* frames_memory=NULL) +
Clone the sequence. +If allocator_ is non-null, call it for all memory allocation and object initialization. +Else, the returned sequence will be destroyed when the original sequence will be destroyed. +If sequence_memory is non-null, puts the class memory-space in it; it must contain +the space given by getSequenceSpace(). +If frames_memory is non-null, use the given memory for frames allocation; it must contain +the space given by getFramesSpace(). +

+ + +

ovirtual void saveXFile(XFile* file) +
Save the usable frames. (n_frames available in frames). +

+ + +

ovirtual void loadXFile(XFile* file) +
Load the usable frames. (n_frames available in frames). +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Sigmoid.html b/torch3/manual/Sigmoid.html new file mode 100644 index 0000000..405147c --- /dev/null +++ b/torch3/manual/Sigmoid.html @@ -0,0 +1,149 @@ + + + + + class Sigmoid + + + + +

class Sigmoid

Sigmoid layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Sigmoid(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Sigmoid layer for GradientMachine. + +

The number of inputs/outputs is the number +of units in the machine. + +

Formally speaking, + +

+
+ + + +
o Sigmoid(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SigmoidKernel.html b/torch3/manual/SigmoidKernel.html new file mode 100644 index 0000000..8930efb --- /dev/null +++ b/torch3/manual/SigmoidKernel.html @@ -0,0 +1,104 @@ + + + + + class SigmoidKernel + + + + +

class SigmoidKernel

Sigmoid Kernel
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SigmoidKernel(real s_, real r_) +

+ +
+

Inherited from Kernel:

+
+

+

Public Methods

+ovirtual real eval(Sequence* x, Sequence* y) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Sigmoid Kernel + +

+
+ + + +
o SigmoidKernel(real s_, real r_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SimpleDecoderSpeechHMM.html b/torch3/manual/SimpleDecoderSpeechHMM.html new file mode 100644 index 0000000..033e41b --- /dev/null +++ b/torch3/manual/SimpleDecoderSpeechHMM.html @@ -0,0 +1,414 @@ + + + + + class SimpleDecoderSpeechHMM + + + + +

class SimpleDecoderSpeechHMM

This class implements a special case of Hidden Markov Models that can be used to do connected word speech recognition for small vocabulary, using embedded training.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]SpeechHMM* model +
The trained SpeechHMM model to decode +
+[more]Grammar* grammar +
the acceptable grammar +
+[more]WordSeg* wordseg +
the object containing target and obtained word sequences +
+[more]real log_word_entrance_penalty +
log word entrance penalty: during viterbi, penalizes large sentences +
+[more]bool forced_alignment +
should we perform forced alignment or real decoding? +
+[more]int* n_previous_states +
for each state, how many previous states +
+[more]int** previous_states +
for each state, the list of previous states +

+ +

+

Public Methods

+[more] SimpleDecoderSpeechHMM(SpeechHMM* model, Grammar* grammar_) +
In order to create a SimpleDecoderSpeechHMM, we need to give a vector of n_models_ HMMs as well as their corresponding name, a lexicon and a grammar, an optional log_word_entrance_penalty and an optional trainer that can be used to initialize each model independently +
+[more]virtual void setDataSet(DataSet* data_) +
this method sets the test data set to be used +
+[more]virtual void logViterbi(Sequence* inputs) +
this method redefine the normal logViterbi class with constraint on word entrance +
+[more]virtual void decode(Sequence* input) +
this method returns the sentence associated to the input +
+[more]virtual void logProbabilities(Sequence* inputs) +
this method computes more efficiently the emission probabilities +
+[more]virtual void setPreviousStates() +
prepare structure previous_states and n_previous_states +
+[more]virtual void prepareTestModel(Sequence* input) +
this method prepare the transition graph associated with a given test sentence +
+[more]virtual int nStatesInGrammar() +
this methods returns the number of states in the grammar +

+ +
+

Inherited from SpeechHMM:

+
+

+

Public Fields

+oint n_models +
+oHMM** models +
+oDataSet* data +
+oEMTrainer** model_trainer +
+oMeasurerList* initial_models_trainer_measurers +
+oLexiconInfo* lexicon +
+oSequence* targets +
+oint add_to_targets +
+obool** word_transitions +
+oint max_n_states +
+oint* states_to_model_states +
+oint* states_to_model +
+oint* states_to_word +
+obool phoneme_targets +

+ +

+

Public Methods

+ovirtual void prepareTrainModel(Sequence* input) +
+ovirtual int addWordToModel(int word, int current_state) +
+ovirtual void addConnectionsBetweenWordsToModel(int word, int next_word, int current_state, int next_current_state, real log_n_next) +
+ovirtual int nStatesInWord(int word) +
+ovirtual int nStatesInWordPronunciation(int word, int pronun) +

+ +
+

Inherited from HMM:

+
+

+

Public Fields

+oint n_states +
+oreal prior_transitions +
+oDistribution** states +
+oDistribution** shared_states +
+oreal** transitions +
+oreal** log_transitions +
+oreal** dlog_transitions +
+oreal** transitions_acc +
+oSequence* log_alpha +
+oSequence* log_beta +
+oSequence* arg_viterbi +
+oint last_arg_viterbi +
+oSequence* viterbi_sequence +
+oSequence* log_probabilities_s +
+obool initialize +

+ +

+

Public Methods

+ovirtual void printTransitions(bool real_values=false, bool transitions_only=false) +
+ovirtual void logAlpha(Sequence* inputs) +
+ovirtual void logBeta(Sequence* inputs) +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class implements a special case of Hidden Markov Models that +can be used to do connected word speech recognition for small +vocabulary, using embedded training. + +

It contains a SpeechHMM and a grammar (which states +the legal sentences of the langage). + +

The decoding is done by creating the whole transition matrix +and hence is not adapted to large vocabulary problems. + +

+
+ + + +
oSpeechHMM* model +
The trained SpeechHMM model to decode +

+ + +

oGrammar* grammar +
the acceptable grammar +

+ + +

oWordSeg* wordseg +
the object containing target and obtained word sequences +

+ + +

oreal log_word_entrance_penalty +
log word entrance penalty: during viterbi, penalizes large sentences +

+ + +

obool forced_alignment +
should we perform forced alignment or real decoding? +

+ + +

oint* n_previous_states +
for each state, how many previous states +

+ + +

oint** previous_states +
for each state, the list of previous states +

+ + +

o SimpleDecoderSpeechHMM(SpeechHMM* model, Grammar* grammar_) +
In order to create a SimpleDecoderSpeechHMM, we need to give a vector of n_models_ +HMMs as well as their corresponding name, a lexicon and a grammar, +an optional log_word_entrance_penalty and an optional trainer that can be +used to initialize each model independently +

+ + +

ovirtual void setDataSet(DataSet* data_) +
this method sets the test data set to be used +

+ + +

ovirtual void logViterbi(Sequence* inputs) +
this method redefine the normal logViterbi class with +constraint on word entrance +

+ + +

ovirtual void decode(Sequence* input) +
this method returns the sentence associated to the input +

+ + +

ovirtual void logProbabilities(Sequence* inputs) +
this method computes more efficiently the emission probabilities +

+ + +

ovirtual void setPreviousStates() +
prepare structure previous_states and n_previous_states +

+ + +

ovirtual void prepareTestModel(Sequence* input) +
this method prepare the transition graph associated with a +given test sentence +

+ + +

ovirtual int nStatesInGrammar() +
this methods returns the number of states in the grammar +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SoftMax.html b/torch3/manual/SoftMax.html new file mode 100644 index 0000000..14cb726 --- /dev/null +++ b/torch3/manual/SoftMax.html @@ -0,0 +1,160 @@ + + + + + class SoftMax + + + + +

class SoftMax

SoftMax layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SoftMax(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
SoftMax layer for GradientMachine. + +

The number of inputs/outputs is the number +of units in the machine. + +

Formally speaking, +where . + +

Options: + +
+"shift" real shift to avoid overflow [0]
+"compute shift" bool compute shift to avoid overflow [false] +
+ +

(you can have the "shift" you want, if you want, or +you can automatically compute the shift) + +

+
+ + + +
o SoftMax(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SoftPlus.html b/torch3/manual/SoftPlus.html new file mode 100644 index 0000000..f09a0e8 --- /dev/null +++ b/torch3/manual/SoftPlus.html @@ -0,0 +1,149 @@ + + + + + class SoftPlus + + + + +

class SoftPlus

SoftPlus layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] SoftPlus(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
SoftPlus layer for GradientMachine. + +

Can be used to constrain the output of a machine to be always positive. +The number of inputs/outputs is the number of units in the machine. + +

Formally speaking, + +

+
+ + + +
o SoftPlus(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Somesimplefunctionsforlogoperations..html b/torch3/manual/Somesimplefunctionsforlogoperations..html new file mode 100644 index 0000000..f5f6ef2 --- /dev/null +++ b/torch3/manual/Somesimplefunctionsforlogoperations..html @@ -0,0 +1,35 @@ + + + + + Some simple functions for log operations. + + + + +

Some simple functions for log operations.

+
+

+
+real logAdd(real log_a, real log_b) +
logAdd(log_a,log_b) = log(a+b) = log(exp(log_a)+exp(log_b)) but done in a smart way so that if log_a or log_b are large but not their difference the computation works correctly +
+real logSub(real log_a, real log_b) +
logSub(log_a,log_b) = log(a-b) +

+ + + +
+

Documentation

+
Some simple functions for log operations. + +

+
+
+
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Somesimplefunctionsforstringoperations..html b/torch3/manual/Somesimplefunctionsforstringoperations..html new file mode 100644 index 0000000..06957d1 --- /dev/null +++ b/torch3/manual/Somesimplefunctionsforstringoperations..html @@ -0,0 +1,40 @@ + + + + + Some simple functions for string operations. + + + + +

Some simple functions for string operations.

+
+

+
+char* strBaseName(char* filename) +
Returns the name of a file without leading pathname. +
+char* strRemoveSuffix(char* filename, char c='.') +
Returns a fresh copy of the name of a file without suffix. +
+char* strConcat(int n, ...) +
Returns the concatenation n strings. +

+ + + +
+

Documentation

+
Some simple functions for string operations. + +

+
+
+
Author:
Samy Bengio (bengio@idiap.ch) +Johnny Mariethoz (Johnny.Mariethoz@idiap.ch) +Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SpatialConvolution.html b/torch3/manual/SpatialConvolution.html new file mode 100644 index 0000000..4ce246a --- /dev/null +++ b/torch3/manual/SpatialConvolution.html @@ -0,0 +1,269 @@ + + + + + class SpatialConvolution + + + + +

class SpatialConvolution

Class for doing convolution over images.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int k_w +
Kernel size (height and width) +
+[more]int d_x +
'x' translation in the input image after each application of the kernel +
+[more]int d_y +
'y' translation in the input image after each application of the kernel +
+[more]int n_input_planes +
Number of input images +
+[more]int n_output_planes +
Number of output images +
+[more]int input_height +
Height of each input image +
+[more]int input_width +
Width of each input image +
+[more]int output_height +
Height of each output image +
+[more]int output_width +
Width of each output image +
+[more]real** weights +
weights[i] means kernel-weights for output plane i. +
+[more]real** der_weights +
Derivatives associated to weights +
+[more]real* biases +
biases[i] is the bias for output plane i +
+[more]real* der_biases +
Derivatives associated to biases +

+ +

+

Public Methods

+[more] SpatialConvolution(int n_input_planes_, int n_output_planes_, int width_, int height_, int k_w_=5, int d_x_=1, int d_y_=1) +
Create a convolution layer +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Class for doing convolution over images. + +

Suppose you put n_input_planes images in each input frame. +The images are in one big vector: each input frame has a size of +n_input_planes*input_height*input_width. (image after image). +Thus, n_inputs = n_input_planes*input_height*input_width. + +

Then, for each output planes, it computes the convolution +of all input image planes with a kernel of size k_w*k_w*n_input_planes. + +

The output image size is computed in the constructor and +put in output_height and output_width. +n_outputs = n_output_planes*output_height*output_width. + +

Note that, depending of the size of your kernel, several (last) columns +or rows of the input image could be lost. + +

Note also that no non-linearity is applied in this layer. + +

+
+ + + +
oint k_w +
Kernel size (height and width) +

+ + +

oint d_x +
'x' translation in the input image after each application of the kernel +

+ + +

oint d_y +
'y' translation in the input image after each application of the kernel +

+ + +

oint n_input_planes +
Number of input images +

+ + +

oint n_output_planes +
Number of output images +

+ + +

oint input_height +
Height of each input image +

+ + +

oint input_width +
Width of each input image +

+ + +

oint output_height +
Height of each output image +

+ + +

oint output_width +
Width of each output image +

+ + +

oreal** weights +
weights[i] means kernel-weights for output plane i. +weights[i] contains n_input_planes times k_w*k_w weights. +

+ + +

oreal** der_weights +
Derivatives associated to weights +

+ + +

oreal* biases +
biases[i] is the bias for output plane i +

+ + +

oreal* der_biases +
Derivatives associated to biases +

+ + +

o SpatialConvolution(int n_input_planes_, int n_output_planes_, int width_, int height_, int k_w_=5, int d_x_=1, int d_y_=1) +
Create a convolution layer +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SpatialSubSampling.html b/torch3/manual/SpatialSubSampling.html new file mode 100644 index 0000000..7462392 --- /dev/null +++ b/torch3/manual/SpatialSubSampling.html @@ -0,0 +1,262 @@ + + + + + class SpatialSubSampling + + + + +

class SpatialSubSampling

Class for doing sub-sampling over images.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int k_w +
Kernel size (height and width) +
+[more]int d_x +
'x' translation in the input image after each application of the kernel +
+[more]int d_y +
'y' translation in the input image after each application of the kernel +
+[more]int n_input_planes +
Number of input images. +
+[more]int input_height +
Height of each input image +
+[more]int input_width +
Width of each input image +
+[more]int output_height +
Height of each output image +
+[more]int output_width +
Width of each output image +
+[more]real* weights +
weights[i] means kernel-weight for output plane i. +
+[more]real* der_weights +
Derivatives associated to weights +
+[more]real* biases +
biases[i] is the bias for output plane i +
+[more]real* der_biases +
Derivatives associated to biases +

+ +

+

Public Methods

+[more] SpatialSubSampling(int n_input_planes_, int width_, int height_, int k_w_=2, int d_x_=2, int d_y_=2) +
Create a sub-sampling layer +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Class for doing sub-sampling over images. + +

Suppose you put n_input_planes images in each input frame. +The images are in one big vector: each input frame has a size of +n_input_planes*input_height*input_width. (image after image). +Thus, n_inputs = n_input_planes*input_height*input_width. + +

Then, for each output planes, it takes its associated input plane +and it computes the convolution of the input image with a kernel +of size k_w*k_w, where the weights of the kernel are equals. + +

The output image size is computed in the constructor and +put in output_height and output_width. +n_outputs = n_input_planes*output_height*output_width. + +

Note that, depending of the size of your kernel, several (last) input columns +or rows of the image could be lost. + +

Note also that no non-linearity is applied in this layer. + +

+
+ + + +
oint k_w +
Kernel size (height and width) +

+ + +

oint d_x +
'x' translation in the input image after each application of the kernel +

+ + +

oint d_y +
'y' translation in the input image after each application of the kernel +

+ + +

oint n_input_planes +
Number of input images. The number of output images in sub-sampling is the same. +

+ + +

oint input_height +
Height of each input image +

+ + +

oint input_width +
Width of each input image +

+ + +

oint output_height +
Height of each output image +

+ + +

oint output_width +
Width of each output image +

+ + +

oreal* weights +
weights[i] means kernel-weight for output plane i. +weights[i] contains only one weight. +

+ + +

oreal* der_weights +
Derivatives associated to weights +

+ + +

oreal* biases +
biases[i] is the bias for output plane i +

+ + +

oreal* der_biases +
Derivatives associated to biases +

+ + +

o SpatialSubSampling(int n_input_planes_, int width_, int height_, int k_w_=2, int d_x_=2, int d_y_=2) +
Create a sub-sampling layer +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SpeechHMM.html b/torch3/manual/SpeechHMM.html new file mode 100644 index 0000000..81bdcca --- /dev/null +++ b/torch3/manual/SpeechHMM.html @@ -0,0 +1,416 @@ + + + + + class SpeechHMM + + + + +

class SpeechHMM

This class implements a special case of Hidden Markov Models that can be used to do connected word speech recognition for small vocabulary, using embedded training.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_models +
the number of basic phoneme models +
+[more]HMM** models +
the basic phoneme models +
+[more]DataSet* data +
a dataset for initialization +
+[more]EMTrainer** model_trainer +
if an initial alignment is given and an emtrainer for each model then it is used to train the models after kmeans during reset +
+[more]MeasurerList* initial_models_trainer_measurers +
as well as a measurer of this trainer +
+[more]LexiconInfo* lexicon +
the acceptable lexicon +
+[more]Sequence* targets +
the current target sequence, with start and end words/phonemes +
+[more]int add_to_targets +
number of words to add +
+[more]bool** word_transitions +
true if the given transition is a transition between words +
+[more]int max_n_states +
the maximum number of states in the graph (used for allocation) +
+[more]int* states_to_model_states +
the relation between model states and SpeechHMM states +
+[more]int* states_to_model +
the relation between models and SpeechHMM states +
+[more]int* states_to_word +
the relation between words and SpeechHMM states +
+[more]bool phoneme_targets +
are targets expressed in words or phonemes? +

+ +

+

Public Methods

+[more] SpeechHMM(int n_models_, HMM** models_, LexiconInfo* lex_, EMTrainer** model_trainer_ = NULL) +
In order to create a SpeechHMM, we need to give a vector of n_models_ HMMs as well as their corresponding name, a lexicon, an optional log_word_entrance_penalty and an optional trainer that can be used to initialize each model independently +
+[more]virtual void prepareTrainModel(Sequence* input) +
this method prepare the transition graph associated with a given training sentence +
+[more]virtual int addWordToModel(int word, int current_state) +
this method is used by prepareTrainModel to prepare the model. +
+[more]virtual void addConnectionsBetweenWordsToModel(int word, int next_word, int current_state, int next_current_state, real log_n_next) +
this method is used by prepareTrainModel to prepare the model. +
+[more]virtual int nStatesInWord(int word) +
this methods returns the number of states in a given word +
+[more]virtual int nStatesInWordPronunciation(int word, int pronun) +
this methods returns the number of states in a given word pronunciation +

+ +
+

Inherited from HMM:

+
+

+

Public Fields

+oint n_states +
+oreal prior_transitions +
+oDistribution** states +
+oDistribution** shared_states +
+oreal** transitions +
+oreal** log_transitions +
+oreal** dlog_transitions +
+oreal** transitions_acc +
+oSequence* log_alpha +
+oSequence* log_beta +
+oSequence* arg_viterbi +
+oint last_arg_viterbi +
+oSequence* viterbi_sequence +
+oSequence* log_probabilities_s +
+obool initialize +

+ +

+

Public Methods

+ovirtual void printTransitions(bool real_values=false, bool transitions_only=false) +
+ovirtual void logAlpha(Sequence* inputs) +
+ovirtual void logBeta(Sequence* inputs) +
+ovirtual void logViterbi(Sequence* inputs) +
+ovirtual void decode(Sequence* input) +
+ovirtual void logProbabilities(Sequence* inputs) +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class implements a special case of Hidden Markov Models that +can be used to do connected word speech recognition for small +vocabulary, using embedded training. + +

It contains a set of phoneme models (represented by HMMs), a lexicon +of words (which are sequences of phonemes) + +

+
+ + + +
oint n_models +
the number of basic phoneme models +

+ + +

oHMM** models +
the basic phoneme models +

+ + +

oDataSet* data +
a dataset for initialization +

+ + +

oEMTrainer** model_trainer +
if an initial alignment is given and an emtrainer for each model +then it is used to train the models after kmeans during reset +

+ + +

oMeasurerList* initial_models_trainer_measurers +
as well as a measurer of this trainer +

+ + +

oLexiconInfo* lexicon +
the acceptable lexicon +

+ + +

oSequence* targets +
the current target sequence, with start and end words/phonemes +

+ + +

oint add_to_targets +
number of words to add +

+ + +

obool** word_transitions +
true if the given transition is a transition between words +

+ + +

oint max_n_states +
the maximum number of states in the graph (used for allocation) +

+ + +

oint* states_to_model_states +
the relation between model states and SpeechHMM states +

+ + +

oint* states_to_model +
the relation between models and SpeechHMM states +

+ + +

oint* states_to_word +
the relation between words and SpeechHMM states +

+ + +

obool phoneme_targets +
are targets expressed in words or phonemes? +

+ + +

o SpeechHMM(int n_models_, HMM** models_, LexiconInfo* lex_, EMTrainer** model_trainer_ = NULL) +
In order to create a SpeechHMM, we need to give a vector of n_models_ +HMMs as well as their corresponding name, a lexicon, +an optional log_word_entrance_penalty and an optional trainer that can be +used to initialize each model independently +

+ + +

ovirtual void prepareTrainModel(Sequence* input) +
this method prepare the transition graph associated with a +given training sentence +

+ + +

ovirtual int addWordToModel(int word, int current_state) +
this method is used by prepareTrainModel +to prepare the model. It adds a given word to the current graph. +

+ + +

ovirtual void addConnectionsBetweenWordsToModel(int word, int next_word, int current_state, int next_current_state, real log_n_next) +
this method is used by prepareTrainModel +to prepare the model. It adds the connections between words. +

+ + +

ovirtual int nStatesInWord(int word) +
this methods returns the number of states in a given word +

+ + +

ovirtual int nStatesInWordPronunciation(int word, int pronun) +
this methods returns the number of states in a given word pronunciation +

+
+
Direct child classes: +
SimpleDecoderSpeechHMM
+
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SpeechMLP.html b/torch3/manual/SpeechMLP.html new file mode 100644 index 0000000..defdefb --- /dev/null +++ b/torch3/manual/SpeechMLP.html @@ -0,0 +1,215 @@ + + + + + class SpeechMLP + + + + +

class SpeechMLP


+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]Linear* hidden_layer_lin +
the first Linear layer +
+[more]GradientMachine* hidden_layer_nonlin +
the first Tanh or Sigmoid layer +
+[more]Linear* output_layer_lin +
the second Linear layer +
+[more]GradientMachine* output_layer_nonlin +
the optional second Softmax, Sigmoid or Tanh layer +
+[more]int n_mlp_hidden +
the number of hidden units +
+[more]int n_mlp_inputs +
the number of inputs +
+[more]int n_mlp_outputs +
the number of outputs +

+ +

+

Public Methods

+[more] SpeechMLP( char* quicknet_mlpw_filename, int n_cw_vecs_=9, char* quicknet_norms_filename=NULL, bool online_norm=false, real alpha_m_=0.005, real alpha_v_=0.005, bool lna8_outputs_=false ) +
Constructor for the SpeechMLP class - reads a Quicknet MLPW format file +

+ +
+

Inherited from ConnectedMachine:

+
+

+

Public Methods

+ovoid addFCL(GradientMachine* machine) +
+ovoid addMachine(GradientMachine* machine) +
+ovoid connectOn(GradientMachine* machine) +
+ovoid addLayer() +
+ovoid build() +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
+ + + +
oLinear* hidden_layer_lin +
the first Linear layer +

+ + +

oGradientMachine* hidden_layer_nonlin +
the first Tanh or Sigmoid layer +

+ + +

oLinear* output_layer_lin +
the second Linear layer +

+ + +

oGradientMachine* output_layer_nonlin +
the optional second Softmax, Sigmoid or Tanh layer +

+ + +

oint n_mlp_hidden +
the number of hidden units +

+ + +

oint n_mlp_inputs +
the number of inputs +

+ + +

oint n_mlp_outputs +
the number of outputs +

+ + +

o SpeechMLP( char* quicknet_mlpw_filename, int n_cw_vecs_=9, char* quicknet_norms_filename=NULL, bool online_norm=false, real alpha_m_=0.005, real alpha_v_=0.005, bool lna8_outputs_=false ) +
Constructor for the SpeechMLP class - reads a Quicknet MLPW format file +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SpeechMLPDistr.html b/torch3/manual/SpeechMLPDistr.html new file mode 100644 index 0000000..bab5411 --- /dev/null +++ b/torch3/manual/SpeechMLPDistr.html @@ -0,0 +1,177 @@ + + + + + class SpeechMLPDistr + + + + +

class SpeechMLPDistr


+ +

Inheritance:

+ + + + + + + +

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Stack.html b/torch3/manual/Stack.html new file mode 100644 index 0000000..1cdbf2b --- /dev/null +++ b/torch3/manual/Stack.html @@ -0,0 +1,116 @@ + + + + + class Stack + + + + +

class Stack

This is an implementation of a "stack".
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Stack() +
Create a stack +
+[more]void push(void* ptr, int size) +
Save size bytes of memory given by ptr +
+[more]void pop() +
Restore the last pushed memory +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This is an implementation of a "stack". +You can "push" an array in memory, which will +be restored when calling "pop", in a stack manner. + +

+
+ + + +
o Stack() +
Create a stack +

+ + +

ovoid push(void* ptr, int size) +
Save size bytes of memory given by ptr +

+ + +

ovoid pop() +
Restore the last pushed memory +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/StochasticGradient.html b/torch3/manual/StochasticGradient.html new file mode 100644 index 0000000..e4f94fc --- /dev/null +++ b/torch3/manual/StochasticGradient.html @@ -0,0 +1,123 @@ + + + + + class StochasticGradient + + + + +

class StochasticGradient

Trainer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] StochasticGradient(GradientMachine* machine_, Criterion* criterion_) +
Take the machine_ to train, the train data_, the criterion_ to use, and the optimizer_ to use +

+ +
+

Inherited from Trainer:

+
+

+

Public Methods

+ovirtual void train(DataSet* data_, MeasurerList* measurers) +
+ovirtual void test(MeasurerList* measurers) +
+ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Trainer for GradientMachine. +Given a machine and a criterion, train the machine using +a stochastic gradient descent. + +

Options: + +
+"end accuracy" real end accuracy [0.0001]
+"learning rate" real learning rate [0.01]
+"learning rate decay" real learning rate decay [0]
+"max iter" int maximum number of iterations [-1]
+"shuffle" bool shuffle the dataset [true] +
+ +

+
+ + + +
o StochasticGradient(GradientMachine* machine_, Criterion* criterion_) +
Take the machine_ to train, the train data_, the criterion_ +to use, and the optimizer_ to use +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/StringCmdOption.html b/torch3/manual/StringCmdOption.html new file mode 100644 index 0000000..3fb2673 --- /dev/null +++ b/torch3/manual/StringCmdOption.html @@ -0,0 +1,128 @@ + + + + + class StringCmdOption + + + + +

class StringCmdOption

This class defines a string command-line option.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] StringCmdOption(const char* name_, char** ptr_, const char* init_value_, const char* help_="", bool save_=false) +

+ +
+

Inherited from CmdOption:

+
+

+

Public Fields

+ochar* name +
+ochar* type_name +
+ochar* help +
+obool save +
+obool is_setted +

+ +

+

Public Methods

+ovirtual void initValue() +
+ovirtual void printValue(XFile* file_) +
+ovirtual void read(int* argc_, char*** argv_) +
+obool isOption(bool set_=false) +
+obool isArgument(bool set_=false) +
+obool isText(bool set_=false) +
+obool isMasterSwitch(bool set_=false) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class defines a string command-line option. + +

+
+ + + +
o StringCmdOption(const char* name_, char** ptr_, const char* init_value_, const char* help_="", bool save_=false) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) + +
See Also:
CmdLine

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/SumMachine.html b/torch3/manual/SumMachine.html new file mode 100644 index 0000000..986009e --- /dev/null +++ b/torch3/manual/SumMachine.html @@ -0,0 +1,155 @@ + + + + + class SumMachine + + + + +

class SumMachine

This machine simply adds up its input vectors.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_machines +
The number of input vectors +

+ +

+

Public Methods

+[more] SumMachine(int n_units, int n_machines_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This machine simply adds up its input vectors. Formally speaking, + where spans the size of the +vectors and spans the number of input vectors. + +

+
+ + + +
oint n_machines +
The number of input vectors +

+ + +

o SumMachine(int n_units, int n_machines_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TableLookupDistribution.html b/torch3/manual/TableLookupDistribution.html new file mode 100644 index 0000000..48689b2 --- /dev/null +++ b/torch3/manual/TableLookupDistribution.html @@ -0,0 +1,230 @@ + + + + + class TableLookupDistribution + + + + +

class TableLookupDistribution

This class outputs one of the observations as the logProbability.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int column +
The column in the observation vector that corresponds to the logProbability +
+[more]bool apply_log +
do we apply a log transformation +
+[more]real prior +
do we normalize by a given prior +

+ +

+

Public Methods

+[more] TableLookupDistribution(int column_ = 0, bool apply_log_ = true, real prior_ = 1.) +
The column number corresponds to the logProbability which can be normalized by an eventual prior +

+ +
+

Inherited from Distribution:

+
+

+

Public Fields

+oreal log_probability +
+oSequence* log_probabilities +

+ +

+

Public Methods

+ovirtual real logProbability(Sequence* inputs) +
+ovirtual real viterbiLogProbability(Sequence* inputs) +
+ovirtual real frameLogProbability(int t, real* f_inputs) +
+ovirtual real viterbiFrameLogProbability(int t, real* f_inputs) +
+ovirtual void eMIterInitialize() +
+ovirtual void iterInitialize() +
+ovirtual void eMSequenceInitialize(Sequence* inputs) +
+ovirtual void sequenceInitialize(Sequence* inputs) +
+ovirtual void eMAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameEMAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void viterbiAccPosteriors(Sequence* inputs, real log_posterior) +
+ovirtual void frameViterbiAccPosteriors(int t, real* f_inputs, real log_posterior) +
+ovirtual void eMUpdate() +
+ovirtual void update() +
+ovirtual void decode(Sequence* inputs) +
+ovirtual void eMForward(Sequence* inputs) +
+ovirtual void viterbiForward(Sequence* inputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void viterbiBackward(Sequence* inputs, Sequence* alpha) +
+ovirtual void frameDecision(int t, real* decision) +

+ +

+

Public Members

+o Returns the decision of the distribution +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class outputs one of the observations as the logProbability. It +can eventually apply a log transformation and/or normalize by a given +prior. It can therefore +be used in conjunction with HMMs to implement the HMM/ANN hybrid model... + +

+
+ + + +
oint column +
The column in the observation vector that corresponds to the +logProbability +

+ + +

obool apply_log +
do we apply a log transformation +

+ + +

oreal prior +
do we normalize by a given prior +

+ + +

o TableLookupDistribution(int column_ = 0, bool apply_log_ = true, real prior_ = 1.) +
The column number corresponds to the logProbability which can +be normalized by an eventual prior +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Tanh.html b/torch3/manual/Tanh.html new file mode 100644 index 0000000..ee4df90 --- /dev/null +++ b/torch3/manual/Tanh.html @@ -0,0 +1,148 @@ + + + + + class Tanh + + + + +

class Tanh

Tanh layer for GradientMachine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Tanh(int n_units) +
Create a layer with n_units units +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Tanh layer for GradientMachine. + +

The number of inputs/outputs is the number +of units for this machine. +Formally speaking, . + +

+
+ + + +
o Tanh(int n_units) +
Create a layer with n_units units +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TemporalConvolution.html b/torch3/manual/TemporalConvolution.html new file mode 100644 index 0000000..936b4af --- /dev/null +++ b/torch3/manual/TemporalConvolution.html @@ -0,0 +1,204 @@ + + + + + class TemporalConvolution + + + + +

class TemporalConvolution

Class for doing a convolution over a sequence.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int k_w +
Kernel size +
+[more]int d_t +
Time translation after one application of the kernel +
+[more]real** weights +
weights[i] means kernel-weights for the i-th component of output frames. +
+[more]real** der_weights +
Derivatives associated to weights +
+[more]real* biases +
biases[i] is the bias for the i-th component of output frames +
+[more]real* der_biases +
Derivatives associated to biases +

+ +

+

Public Methods

+[more] TemporalConvolution(int input_frame_size, int output_frame_size, int k_w_=5, int d_t_=1) +
Create a convolution layer +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Class for doing a convolution over a sequence. + +

For each component of output frames, it computes the convolution +of the input sequence with a kernel of size k_w (over the time). + +

Note that, depending of the size of your kernel, several (last) frames +of the input sequence could be lost. + +

Note also that no non-linearity is applied in this layer. + +

+
+ + + +
oint k_w +
Kernel size +

+ + +

oint d_t +
Time translation after one application of the kernel +

+ + +

oreal** weights +
weights[i] means kernel-weights for the i-th component of output frames. +weights[i] contains input_frame_size times k_w weights. +

+ + +

oreal** der_weights +
Derivatives associated to weights +

+ + +

oreal* biases +
biases[i] is the bias for the i-th component of output frames +

+ + +

oreal* der_biases +
Derivatives associated to biases +

+ + +

o TemporalConvolution(int input_frame_size, int output_frame_size, int k_w_=5, int d_t_=1) +
Create a convolution layer +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TemporalMean.html b/torch3/manual/TemporalMean.html new file mode 100644 index 0000000..6227c7f --- /dev/null +++ b/torch3/manual/TemporalMean.html @@ -0,0 +1,144 @@ + + + + + class TemporalMean + + + + +

class TemporalMean

Given an input sequence, it does the mean over all input frames.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] TemporalMean(int input_frame_size) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Given an input sequence, it does the mean over all +input frames. Thus, the output sequence will have only +one frame, which has the same size than input frames. + +

+
+ + + +
o TemporalMean(int input_frame_size) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TemporalSubSampling.html b/torch3/manual/TemporalSubSampling.html new file mode 100644 index 0000000..232a6fa --- /dev/null +++ b/torch3/manual/TemporalSubSampling.html @@ -0,0 +1,205 @@ + + + + + class TemporalSubSampling + + + + +

class TemporalSubSampling

Class for doing sub-sampling over a sequence.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int k_w +
Kernel size +
+[more]int d_t +
Time translation after one application of the kernel +
+[more]real* weights +
weights[i] means kernel-weights for the i-th component of output frames. +
+[more]real* der_weights +
Derivatives associated to weights +
+[more]real* biases +
biases[i] is the bias for the i-th component of output frames +
+[more]real* der_biases +
Derivatives associated to biases +

+ +

+

Public Methods

+[more] TemporalSubSampling(int input_frame_size, int k_w_=2, int d_t_=2) +
Create a sub-sampling layer +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Class for doing sub-sampling over a sequence. + +

Then, for each component of output frames, it takes its associated input component +and it computes the convolution of the input sequence with a kernel +of size k_w, over the time, where the weights of the kernel are equals. + +

Note that, depending of the size of your kernel, several (last) frames +of the input seqience could be lost. + +

Note also that no non-linearity is applied in this layer. + +

+
+ + + +
oint k_w +
Kernel size +

+ + +

oint d_t +
Time translation after one application of the kernel +

+ + +

oreal* weights +
weights[i] means kernel-weights for the i-th component of output frames. +weights[i] contains only one weight. +

+ + +

oreal* der_weights +
Derivatives associated to weights +

+ + +

oreal* biases +
biases[i] is the bias for the i-th component of output frames +

+ + +

oreal* der_biases +
Derivatives associated to biases +

+ + +

o TemporalSubSampling(int input_frame_size, int k_w_=2, int d_t_=2) +
Create a sub-sampling layer +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Textoutputsfunctions..html b/torch3/manual/Textoutputsfunctions..html new file mode 100644 index 0000000..4993272 --- /dev/null +++ b/torch3/manual/Textoutputsfunctions..html @@ -0,0 +1,47 @@ + + + + + Text outputs functions. + + + + +

Text outputs functions.

+
+
+
+ +o +error
Print an error message. +
+ +o +warning
Print a warning message +
+ +o +message
Print a message +
+ +o +print
Like printf +
+ +o +controlBar
Print a control bar [##########]. +
+ +
Text outputs functions. + +

These functions are like printf(), but you should +use them instead. Note that you should never try to +print a message larger than 10000 characters. + +

+
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index Hierarchy of classes


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TimeMeasurer.html b/torch3/manual/TimeMeasurer.html new file mode 100644 index 0000000..48aa2a4 --- /dev/null +++ b/torch3/manual/TimeMeasurer.html @@ -0,0 +1,123 @@ + + + + + class TimeMeasurer + + + + +

class TimeMeasurer

Measure the time (in seconds) between two measureIteration() calls.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] TimeMeasurer(DataSet* data_, XFile* file_) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Measure the time (in seconds) between +two measureIteration() calls. + +

Save in file the sum of these time, +at each iteration. + +

+
+ + + +
o TimeMeasurer(DataSet* data_, XFile* file_) +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Timer.html b/torch3/manual/Timer.html new file mode 100644 index 0000000..23e300e --- /dev/null +++ b/torch3/manual/Timer.html @@ -0,0 +1,145 @@ + + + + + class Timer + + + + +

class Timer

Timer.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Timer() +
Create the timer and start it now! +
+[more]void reset() +
Reset the timer. +
+[more]void stop() +
Stop the timer. +
+[more]void resume() +
Resume the timer. +
+[more]real getTime() +
Get the total accumulated time. +
+[more]static real getRunTime() +
System dependent function which returns time elapsed since an arbitrary point reference in the past +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Timer. to measure time. +It accumulates the time measured in several resume() (or +constructor definition) and stop() calls. + +

Use getTime() to know this accumulated time. + +

+
+ + + +
o Timer() +
Create the timer and start it now! +

+ + +

ovoid reset() +
Reset the timer. The timer will count time starting +from now, and the accumulated time is erased. +

+ + +

ovoid stop() +
Stop the timer. Updates accumulated time. +

+ + +

ovoid resume() +
Resume the timer. It will count time starting from now. +

+ + +

oreal getTime() +
Get the total accumulated time. (Until now, if the +timer is still running. +

+ + +

ostatic real getRunTime() +
System dependent function which returns time elapsed +since an arbitrary point reference in the past +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Trainer.html b/torch3/manual/Trainer.html new file mode 100644 index 0000000..ac25fe4 --- /dev/null +++ b/torch3/manual/Trainer.html @@ -0,0 +1,165 @@ + + + + + class Trainer + + + + +

class Trainer

Trainer.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] Trainer(Machine* machine_) +
+[more]virtual void train(DataSet* data_, MeasurerList* measurers) = 0 +
Train the machine. +
+[more]virtual void test(MeasurerList* measurers) +
Test the machine. +
+[more]static Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
Make a table of measurers from a List. +
+[more]virtual void loadXFile(XFile* file) +
By default, just load the machine +
+[more]virtual void saveXFile(XFile* file) +
By default, just save the machine +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Trainer. + +

A trainer takes a Machine and is able to train this machine on a given dataset +with the train() method. +For each machine, it should exist a trainer which knows how to train this machine. +Testing the machine is possible with the test() method. + +

+
+ + + +
o Trainer(Machine* machine_) +

+ + +

ovirtual void train(DataSet* data_, MeasurerList* measurers) = 0 +
Train the machine. +The Trainer has to call the measurers +when it want. +

+ + +

ovirtual void test(MeasurerList* measurers) +
Test the machine. +This method call all the measurers, +for all the examples of their associated +dataset. +It's already written... +

+ + +

ostatic Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas) +
Make a table of measurers from a List. + +

Given a List of measurers, +and, if you want, a train DataSet (else NULL) +

    +
  • Returns all datasets associated to the measurers in datas. +For i != j, (*datas)[i] != (*datas)[j]. +Moreover, if train != NULL, (*datas)[0] = train. +
  • Returns the list of measurers associated to (*datas)[i] in (*meas)[i]. +
  • Returns the number of measureurs associated to (*datas)[i] in (*n_meas)[i]. +
  • Returns in *n_datas the number of datasets in *datas. +
+ +

Returns an allocator to all the memory allocated by the function. +You have to delete this allocator by yourself. +

+ + +

ovirtual void loadXFile(XFile* file) +
By default, just load the machine +

+ + +

ovirtual void saveXFile(XFile* file) +
By default, just save the machine +

+
+
Direct child classes: +
StochasticGradient
+QCTrainer
+NPTrainer
+EMTrainer
+Boosting
+BayesClassifier
+Bagging
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/TwoClassFormat.html b/torch3/manual/TwoClassFormat.html new file mode 100644 index 0000000..5b3981a --- /dev/null +++ b/torch3/manual/TwoClassFormat.html @@ -0,0 +1,127 @@ + + + + + class TwoClassFormat + + + + +

class TwoClassFormat

Define the two class encoding format.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] TwoClassFormat(DataSet* data) +
Autodetect classes +
+[more] TwoClassFormat(real class_1, real class_2) +
Specify the label of the classes +

+ +
+

Inherited from ClassFormat:

+
+

+

Public Fields

+oint n_classes +
+oreal** class_labels +

+ +

+

Public Methods

+ovirtual int getOutputSize() +
+ovirtual void fromOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual void toOneHot(real* outputs, real* one_hot_outputs) +
+ovirtual int getClass(real* vector) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Define the two class encoding format. + +

+
+ + + +
o TwoClassFormat(DataSet* data) +
Autodetect classes +

+ + +

o TwoClassFormat(real class_1, real class_2) +
Specify the label of the classes +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Vec.html b/torch3/manual/Vec.html new file mode 100644 index 0000000..fc9e812 --- /dev/null +++ b/torch3/manual/Vec.html @@ -0,0 +1,184 @@ + + + + + class Vec + + + + +

class Vec

Vector object.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n +
Size of the vector +
+[more]real* ptr +
Data of the vector +

+ +

+

Public Methods

+[more] Vec(real* ptr_, int n_dim) +
Create a vector from values in ptr_. +
+[more] Vec(int n_dim) +
Create a new vector +
+[more]void copy(Vec* vec, int start_i = 0) +
Copy the vector vec starting from index start_i +
+[more]void zero() +
Zero the matrix +
+[more]real norm1(Vec* weights = NULL) +
Compute the norm1 +
+[more]real norm2(Vec* weights = NULL) +
Compute the norm2 +
+[more]real normInf() +
Compute the norm inf +
+[more]real iP(Vec* vec, int start_i = 0) +
Inner product of two vectors from start_i downwards +
+[more]Vec* subVec(int dim1, int dim2) +
Return a sub-vector. +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Vector object. + +

+
+ + + +
oint n +
Size of the vector +

+ + +

oreal* ptr +
Data of the vector +

+ + +

o Vec(real* ptr_, int n_dim) +
Create a vector from values in ptr_. +(No memory copy). +

+ + +

o Vec(int n_dim) +
Create a new vector +

+ + +

ovoid copy(Vec* vec, int start_i = 0) +
Copy the vector vec starting from index start_i +

+ + +

ovoid zero() +
Zero the matrix +

+ + +

oreal norm1(Vec* weights = NULL) +
Compute the norm1 +

+ + +

oreal norm2(Vec* weights = NULL) +
Compute the norm2 +

+ + +

oreal normInf() +
Compute the norm inf +

+ + +

oreal iP(Vec* vec, int start_i = 0) +
Inner product of two vectors from start_i downwards +

+ + +

oVec* subVec(int dim1, int dim2) +
Return a sub-vector. +Note that the memory is shared with the original +vector, so *be carefull*. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/Vocabulary.html b/torch3/manual/Vocabulary.html new file mode 100644 index 0000000..bbdb529 --- /dev/null +++ b/torch3/manual/Vocabulary.html @@ -0,0 +1,160 @@ + + + + + class Vocabulary + + + + +

class Vocabulary

This object contains the list of words we want our recogniser to recognise plus a few "special" words (eg.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more]char* getWord( int index ) +
Returns the word given the index into the vocabulary +

+ +

+

Public Members

+[more] Creates the vocabulary +
+[more] 'lex_fname' is the name of the lexicon file containing the pronunciations to be +
+[more] recognised. +
+[more] where the (prior) is optional +
+[more] 'sent_start_word' and 'sent_end_word' are the words that will start and +
+[more] Adds a word to the vocabulary. +
+[more] Returns the index of a given word. +
+[more] words at indices of 'guess' and 'guess+1' are checked for a match +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
+This object contains the list of words we want our recogniser to recognise +plus a few "special" words (eg. sentence markers, silence word). There are +no duplicates in the list, and the list is sorted alphabetically. + +

+
+ + + +
o Creates the vocabulary +
Creates the vocabulary +

+ + +

o 'lex_fname' is the name of the lexicon file containing the pronunciations to be +
'lex_fname' is the name of the lexicon file containing the pronunciations to be +

+ + +

o recognised. +
recognised. The format is the standard "word(prior) ph ph ph" format +

+ + +

o where the (prior) is optional +
where the (prior) is optional +

+ + +

o 'sent_start_word' and 'sent_end_word' are the words that will start and +
'sent_start_word' and 'sent_end_word' are the words that will start and +

+ + +

o Adds a word to the vocabulary. +
Adds a word to the vocabulary. Maintains alphabetic order. Does not add +

+ + +

ochar* getWord( int index ) +
Returns the word given the index into the vocabulary +

+ + +

o Returns the index of a given word. +
Returns the index of a given word. If 'guess' is defined, then the +

+ + +

o words at indices of 'guess' and 'guess+1' are checked for a match +
words at indices of 'guess' and 'guess+1' are checked for a match +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/WeightedMSECriterion.html b/torch3/manual/WeightedMSECriterion.html new file mode 100644 index 0000000..2597d0e --- /dev/null +++ b/torch3/manual/WeightedMSECriterion.html @@ -0,0 +1,189 @@ + + + + + class WeightedMSECriterion + + + + +

class WeightedMSECriterion

Similar to MSECriterion, but you can put a weight on each example.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]real* weights +
Pointer on the weights. +

+ +

+

Public Methods

+[more] WeightedMSECriterion(DataSet* data_) +
With this constructor, the weights are allocated and initializated to 1 +
+[more] WeightedMSECriterion(DataSet* data_, real* weights_) +
With this constructor, you provide the weights. +

+ +
+

Inherited from Criterion:

+
+

+

Public Fields

+oDataSet* data +

+ +

+

Public Methods

+ovirtual void setDataSet(DataSet* data_) +

+ +
+

Inherited from GradientMachine:

+
+

+

Public Fields

+oint n_inputs +
+oint n_outputs +
+oParameters* params +
+oParameters* der_params +
+oSequence* beta +

+ +

+

Public Methods

+ovirtual void iterInitialize() +
+ovirtual void forward(Sequence* inputs) +
+ovirtual void backward(Sequence* inputs, Sequence* alpha) +
+ovirtual void setPartialBackprop(bool flag=true) +
+ovirtual void frameForward(int t, real* f_inputs, real* f_outputs) +
+ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Similar to MSECriterion, but you +can put a weight on each example. + +

Options: + +
+"average frame size" bool divided by the frame size [true] +
+ +

+
+ + + +
oreal* weights +
Pointer on the weights. +You can modify the weights when you want. + +

The length of weights is the +n_real_examples of data. +

+ + +

o WeightedMSECriterion(DataSet* data_) +
With this constructor, the weights are allocated +and initializated to 1 +

+ + +

o WeightedMSECriterion(DataSet* data_, real* weights_) +
With this constructor, you provide the weights. + +

The length of weights must be the +n_real_examples of data. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/WeightedSumMachine.html b/torch3/manual/WeightedSumMachine.html new file mode 100644 index 0000000..93079ce --- /dev/null +++ b/torch3/manual/WeightedSumMachine.html @@ -0,0 +1,184 @@ + + + + + class WeightedSumMachine + + + + +

class WeightedSumMachine

Weighted-sum machine.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]int n_outputs +
Output frame size +
+[more]Trainer** trainers +
The trainers used in the combination +
+[more]MeasurerList** trainers_measurers +
The corresponding measurers +
+[more]int n_trainers +
The number of trainers in the combination +
+[more]int n_trainers_trained +
The number of trainers that have been already trained. +
+[more]real* weights +
The weights of the combination +
+[more]bool weights_is_allocated +
True if the weights aren't given by the user, false otherwise +

+ +

+

Public Methods

+[more] WeightedSumMachine(Trainer** trainer_, int n_trainers_, MeasurerList** trainers_measurers, real* weights_=NULL) +
trainers_measurers is an array which possibly specify the measurers which should be given to the corresponding trainer when training. +

+ +
+

Inherited from Machine:

+
+

+

Public Fields

+oSequence* outputs +

+ +

+

Public Methods

+ovirtual void forward(Sequence* sequence) +
+ovirtual void reset() +
+ovirtual void setDataSet(DataSet* dataset_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
Weighted-sum machine. +This class contains a series of Trainers, and its forward method +simply performs the average of the output of each machine associated to +the trainer on the same input. + +

+
+ + + +
oint n_outputs +
Output frame size +

+ + +

oTrainer** trainers +
The trainers used in the combination +

+ + +

oMeasurerList** trainers_measurers +
The corresponding measurers +

+ + +

oint n_trainers +
The number of trainers in the combination +

+ + +

oint n_trainers_trained +
The number of trainers that have been already trained. +After the initialization, it's zero. +Note that the forward method depends on this value. +(only the first n_trainers_trained trainers are used) +

+ + +

oreal* weights +
The weights of the combination +

+ + +

obool weights_is_allocated +
True if the weights aren't given by the user, false otherwise +

+ + +

o WeightedSumMachine(Trainer** trainer_, int n_trainers_, MeasurerList** trainers_measurers, real* weights_=NULL) +
trainers_measurers is an array which possibly specify the measurers which +should be given to the corresponding trainer when training. +If weights_ isn't specified, weights are setted to zero. +

+ +
This class has no child classes.
+ +
Author:
Ronan Collobert (collober@idiap.ch) +
See Also:
Bagging +
Boosting +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/WordChainElemPool.html b/torch3/manual/WordChainElemPool.html new file mode 100644 index 0000000..71cdbf9 --- /dev/null +++ b/torch3/manual/WordChainElemPool.html @@ -0,0 +1,93 @@ + + + + + class WordChainElemPool + + + + +

class WordChainElemPool

This class is a pool of pre-allocated WordChainElem structures.
+
+ +
+

+

Public Methods

+[more]void returnElem( WordChainElem* elem ) +
Returns a WordChainElem instance that is no longer required to the pool +

+ +

+

Public Members

+[more] Creates the pool. +
+[more] 'max_size' is the initial size of the pool +
+[more] 'realloc_amount_' is the number of additional WordChainElem instances +
+[more] that are to be allocated each time the pool empties +
+[more] If 'realloc_amount_' is undefined, then 'max_size' elements are +
+[more] Gets the next free WordChainElem instance from the pool. +

+ +
+ + +
+

Documentation

+
+This class is a pool of pre-allocated WordChainElem structures. It's +purpose is to enable fast access to the WordChainElem instances during +decoding. If the pool is empty, and something asks for a WordChainElem +instance then a block of new instances are allocated before the requested +instance is returned. + +

+
+ + + +
o Creates the pool. +
Creates the pool. +

+ + +

o 'max_size' is the initial size of the pool +
'max_size' is the initial size of the pool +

+ + +

o 'realloc_amount_' is the number of additional WordChainElem instances +
'realloc_amount_' is the number of additional WordChainElem instances +

+ + +

o that are to be allocated each time the pool empties +
that are to be allocated each time the pool empties +

+ + +

o If 'realloc_amount_' is undefined, then 'max_size' elements are +
If 'realloc_amount_' is undefined, then 'max_size' elements are +

+ + +

o Gets the next free WordChainElem instance from the pool. +
Gets the next free WordChainElem instance from the pool. Allocates +

+ + +

ovoid returnElem( WordChainElem* elem ) +
Returns a WordChainElem instance that is no longer required to the pool +

+ +
This class has no child classes.
+ +
Author:
Darren Moore (moore@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/WordSeg.html b/torch3/manual/WordSeg.html new file mode 100644 index 0000000..f33bd8c --- /dev/null +++ b/torch3/manual/WordSeg.html @@ -0,0 +1,163 @@ + + + + + class WordSeg + + + + +

class WordSeg

This class keeps track of all information to compute word errors
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]LexiconInfo* lexicon +
the corresponding lexicon +
+[more]int* target_word_sequence +
the target word sequence +
+[more]int target_word_sequence_size +
the length of the target word sequence +
+[more]int target_word_sequence_max_size +
the length of the longest target word sequence +
+[more]int* word_sequence +
the word sequence +
+[more]int word_sequence_size +
the length of the word sequence +
+[more]int word_sequence_max_size +
the length of the longest word sequence +
+[more]int* word_sequence_time +
the starting time of each word of the word sequence +

+ +

+

Public Methods

+[more] WordSeg(LexiconInfo* lexicon_) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class keeps track of all information to compute word errors + +

+
+ + + +
oLexiconInfo* lexicon +
the corresponding lexicon +

+ + +

oint* target_word_sequence +
the target word sequence +

+ + +

oint target_word_sequence_size +
the length of the target word sequence +

+ + +

oint target_word_sequence_max_size +
the length of the longest target word sequence +

+ + +

oint* word_sequence +
the word sequence +

+ + +

oint word_sequence_size +
the length of the word sequence +

+ + +

oint word_sequence_max_size +
the length of the longest word sequence +

+ + +

oint* word_sequence_time +
the starting time of each word of the word sequence +

+ + +

o WordSeg(LexiconInfo* lexicon_) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/WordSegMeasurer.html b/torch3/manual/WordSegMeasurer.html new file mode 100644 index 0000000..738404d --- /dev/null +++ b/torch3/manual/WordSegMeasurer.html @@ -0,0 +1,188 @@ + + + + + class WordSegMeasurer + + + + +

class WordSegMeasurer

This class can be used to save the word segmentation of a SimpleDecoderSpeechHMM in a file.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Fields

+[more]WordSeg* wordseg +
the pointer to the corresponding wordseg object +
+[more]bool print_obtained +
a boolean stating whether we print the obtained word sequence +
+[more]bool print_targets +
a boolean stating whether we also print the corresponding targets +
+[more]bool print_timing +
a boolean stating whether we also print the alignment timings +
+[more]bool print_desired_timing +
a boolean stating whether we also print the desired alignment timings +
+[more]int n_per_frame +
when timing is required, what is the number of tics per frames +
+[more]EditDistance* edit_distance +
eventually compute the edit_distance +
+[more]EditDistance* sum_edit_distance +
. +

+ +

+

Public Methods

+[more] WordSegMeasurer(WordSeg* wordseg_, DataSet* data_, XFile* file_, EditDistance* edit_distance_=NULL, char** file_list_=NULL, int n_file_list_ = 0) +

+ +
+

Inherited from Measurer:

+
+

+

Public Fields

+oXFile* file +
+oDataSet* data +
+obool binary_mode +

+ +

+

Public Methods

+ovirtual void measureExample() +
+ovirtual void measureIteration() +
+ovirtual void measureEnd() +
+ovirtual void reset() +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
This class can be used to save the word segmentation of a +SimpleDecoderSpeechHMM +in a file. Optionally, it also prints the corresponding target segmentation. + +

+
+ + + +
oWordSeg* wordseg +
the pointer to the corresponding wordseg object +

+ + +

obool print_obtained +
a boolean stating whether we print the obtained word sequence +

+ + +

obool print_targets +
a boolean stating whether we also print the corresponding targets +

+ + +

obool print_timing +
a boolean stating whether we also print the alignment timings +

+ + +

obool print_desired_timing +
a boolean stating whether we also print the desired alignment timings +

+ + +

oint n_per_frame +
when timing is required, what is the number of tics per frames +

+ + +

oEditDistance* edit_distance +
eventually compute the edit_distance +

+ + +

oEditDistance* sum_edit_distance +
. and keep its sum +

+ + +

o WordSegMeasurer(WordSeg* wordseg_, DataSet* data_, XFile* file_, EditDistance* edit_distance_=NULL, char** file_list_=NULL, int n_file_list_ = 0) +

+ +
This class has no child classes.
+ +
Author:
Samy Bengio (bengio@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/XFile.html b/torch3/manual/XFile.html new file mode 100644 index 0000000..b80e602 --- /dev/null +++ b/torch3/manual/XFile.html @@ -0,0 +1,201 @@ + + + + + class XFile + + + + +

class XFile

XFile.
+
+ +

Inheritance:

+ + + + + + + +
+ +
+

+

Public Methods

+[more] XFile() +
+[more]virtual int read(void* ptr, int block_size, int n_blocks) = 0 +
Read something +
+[more]virtual int write(void* ptr, int block_size, int n_blocks) = 0 +
Write +
+[more]int taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
Read and check the tag/the size. +
+[more]int taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
Write and write the tag/the size +
+[more]virtual int eof() = 0 +
Are we at the end ? +
+[more]virtual int flush() = 0 +
Flush the file +
+[more]virtual int seek(long offset, int whence) = 0 +
Seek +
+[more]virtual long tell() = 0 +
Tell me where am I +
+[more]virtual void rewind() = 0 +
Rewind +
+[more]virtual int printf(const char* format, ...) = 0 +
Print some text +
+[more]virtual int scanf(const char* format, void* ptr) = 0 +
Scan some text +
+[more]virtual char* gets(char* dest, int size_) = 0 +
Get one line (read at most size_ characters) +

+ +
+

Inherited from Object:

+
+

+

Public Fields

+oAllocator* allocator +

+ +

+

Public Methods

+ovoid addOption(const char* name, int size, void* ptr, const char* help="") +
+ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="") +
+ovoid addROption(const char* name, real* ptr, real init_value, const char* help="") +
+ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="") +
+ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="") +
+ovoid setOption(const char* name, void* ptr) +
+ovoid setIOption(const char* name, int option) +
+ovoid setROption(const char* name, real option) +
+ovoid setBOption(const char* name, bool option) +
+ovoid setOOption(const char* name, Object* option) +
+ovirtual void loadXFile(XFile* file) +
+ovirtual void saveXFile(XFile* file) +
+ovoid load(const char* filename) +
+ovoid save(const char* filename) +
+ovoid* operator new(size_t size, Allocator* allocator_=NULL) +
+ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_) +
+ovoid operator delete(void* ptr) +

+ +
+ + +
+

Documentation

+
XFile. A File which could be anything. +The syntax (and results) for method is very similar +to C FILE. (Except for the FILE pointer which is not +given in the parameters!). + +

+
+ + + +
o XFile() +

+ + +

ovirtual int read(void* ptr, int block_size, int n_blocks) = 0 +
Read something +

+ + +

ovirtual int write(void* ptr, int block_size, int n_blocks) = 0 +
Write +

+ + +

oint taggedRead(void* ptr, int block_size, int n_blocks, const char* tag) +
Read and check the tag/the size. To be used with taggedWrite(). +If the tag and the size readed doesn't correspond to the given +tag and size, an error will occur. +

+ + +

oint taggedWrite(void* ptr, int block_size, int n_blocks, const char* tag) +
Write and write the tag/the size +

+ + +

ovirtual int eof() = 0 +
Are we at the end ? +

+ + +

ovirtual int flush() = 0 +
Flush the file +

+ + +

ovirtual int seek(long offset, int whence) = 0 +
Seek +

+ + +

ovirtual long tell() = 0 +
Tell me where am I +

+ + +

ovirtual void rewind() = 0 +
Rewind +

+ + +

ovirtual int printf(const char* format, ...) = 0 +
Print some text +

+ + +

ovirtual int scanf(const char* format, void* ptr) = 0 +
Scan some text +

+ + +

ovirtual char* gets(char* dest, int size_) = 0 +
Get one line (read at most size_ characters) +

+
+
Direct child classes: +
NullXFile
+MemoryXFile
+DiskXFile
+
+ +
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/controlBar.html b/torch3/manual/controlBar.html new file mode 100644 index 0000000..bba8a85 --- /dev/null +++ b/torch3/manual/controlBar.html @@ -0,0 +1,30 @@ + + + + + void controlBar + + + + +

void controlBar

(int level, int max_level)

Print a control bar [##########].
+ + +
+

Documentation

+
Print a control bar [##########]. + +

First time, you can it with level=-1. +It'll print the control bar at each time +you will call that. + +

max_level is the value of the last level +you'll call this function. + +

+
Author:
Ronan Collobert (collober@idiap.ch) +

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/error.html b/torch3/manual/error.html new file mode 100644 index 0000000..8840e61 --- /dev/null +++ b/torch3/manual/error.html @@ -0,0 +1,20 @@ + + + + + void error + + + + +

void error

(const char* msg, ...)

Print an error message.
+ + +
+

Documentation

+
Print an error message. The program will exit.
+

Alphabetic index HTML hierarchy of classes or Java


+
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LogOutputsExpert_2, ...}$ +7:$1-p$ +45:$\sum_j alpha_j y_j = 1$ +26:$ouputs[i] = log(1/(1+exp(-inputs[i])))$ +42:$k(x,y) = exp(-g * ||x-y||^2)$ +29:$outputs[i] = \sum_j a_j * inputs_j[i]$ +47:$y$ +48:$Cdown$ +18:$w_{ij}$ +51:$alpha_j$ +21:$\sum_i,j w_{ij}^2 + sum_i b_i^2$ +13:$o_i$ +17:$ouputs[i] = \sum_j w_{ij} inputs[i] + b_i$ +60:$(w,b)$ +12:$ p(x) = \frac{1}{N}\sum_i \frac{1}{(2 \Pi var)^{d/2}} \exp(- \frac{||x - x_i||^2}{2 var})$ +70:$ y(x) = \frac{\sum_i t_i \exp(- \frac{||x - x_i||^2}{2 var})}{\sum_i \exp(- \frac{||x - x_i||^2}{2 var})}$ +55:$q_{ij} = k(x_i, x_j)$ +67:$+ \sum_j C_(j+n) |y_j -w.x_j-b -eps|_+$ +24:$LogInputs_j$ +39:$j$ +40:$ouputs[i] = tanh(inputs[i])$ +65:$C_j$ +68:$n$ +37:$ouputs[i] = log(1+exp(inputs[i]))$ +16:$ouputs[i] = exp(inputs[i])$ +31:$inputs_j$ +43:$k(x,y) = tanh(s*xy+r)$ +36:$a = \sum_j exp(inputs[j]-shift)$ +27:$ouputs[i] = log(1/a * exp(inputs[i]))$ +38:$outputs[i] = \sum_j inputs_j[i]$ +53:$Cdown_j$ +69:$C$ +54:$beta$ 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zcmZ?wbhEHbvUV_sg0vVRlep zUT#ibUH$CLjP97|8hg8t^_%zaId~E%=;f7aZRKxk>swYjH7c^q#Kc`$*&sZ;+`~Ol zL*3NdE7jE{7APVst6^&DtgCA)C##W~TG-k;MN7*vC@7wR8bI+U3nR!J9S{NX69Zea zLqmawj#U4Vh6DovmcEvzg9Q#M9Ii(X9muedZ+!$E~PkE!<|b>N=j+E$MO{}jttfS DX0}r~ literal 0 HcmV?d00001 diff --git a/torch3/manual/index.html b/torch3/manual/index.html new file mode 100644 index 0000000..84c339e --- /dev/null +++ b/torch3/manual/index.html @@ -0,0 +1,187 @@ + + +

Torch Reference Manual +
[Torch] +
http://www.torch.ch +
+ +

Table of Contents

+

General stuff

+ +

Namespaces

+ +

Classes

+
    +
  • Allocator Class do easily allocate/deallocate memory in Torch. +
  • Bagging This class represents a Trainer that implements the well-known Bagging algorithm (Breiman, 1996). +
  • BayesClassifier A multi class bayes classifier -- maximizes the likelihood of each class separately using a trainer for distribution. +
  • BayesClassifierMachine BayesClassifierMachine is the machine used by the BayesClassifier trainer to perform a Bayes Classification using different distributions. +
  • BeamSearchDecoder This class implements a Viterbi decoder with beam search capabilities. +
  • BoolCmdOption This class defines a bool command-line option. +
  • Boosting Boosting implementation. +
  • BoostingMeasurer Compute the classification weighted error (in %) for BoostingMachine of the inputs with respect to the targets of data. +
  • ClassFormat Used to define a class code. +
  • ClassFormatDataSet Given a DataSet, convert (on-the-fly) targets using a conversion table. +
  • ClassMeasurer Compute the classification error (in %) of the inputs with respect to the targets of data. +
  • ClassNLLCriterion This criterion can be used to train *in classification* a GradientMachine object using the StochasticGradient trainer. +
  • ClassNLLMeasurer This class measures the negative log likelihood. +
  • CmdLine This class provides a useful interface for the user, to easily read some arguments/options from the command-line. +
  • CmdOption This class defines an option for the command line. +
  • ConnectedMachine Easy connections between several GradientMachine. +
  • Criterion Criterion class for StochasticGradient. +
  • DataSet Provides an interface to manipulate all kind of data. +
  • DecoderBatchTest This class is used to decode a set of test files and display statistics and results for each file (ie. +
  • DecoderSingleTest This class is used to recognise a single input data file, post-process the recognition result and output the result. +
  • DecodingHMM This class contains all HMM information required for decoding. +
  • DecodingHypothesis This class contains all hypothesis data that needs to be updated and propagated as hypotheses are extended through word models and across word boundaries. +
  • DiagonalGMM This class can be used to model Diagonal Gaussian Mixture Models. +
  • DiskDataSet Provides an interface to manipulate all kind of data which are kept on disk, and not fully loaded in memory. +
  • DiskHTKDataSet Provides an interface to manipulate HTK data which are kept on disk, and not fully loaded in memory. +
  • DiskMatDataSet Matrix DataSet On Disk. +
  • DiskXFile A file on the disk. +
  • Distribution This class is designed to handle generative distribution models such as Gaussian Mixture Models and Hidden Markov Models. +
  • DotKernel DotProduct Kernel. +
  • EMTrainer This class is used to train any distribution using the EM algorithm. +
  • EditDistance This class can be used to compute the "edit distance" between two sequences. +
  • EditDistanceMeasurer This class can be used to measure and print an EditDistance object. +
  • ExampleFrameSelectorDataSet This dataset is empty at the begining. +
  • Exp Exponentiel layer for GradientMachine. +
  • FileListCmdOption This class take a file name in the command line, and reads a list of files contained in this file. +
  • FrameSeg This class keeps track of all information to compute errors at the frame level +
  • FrameSegMeasurer This class can be used to save the frame segmentation of a SimpleDecoderSpeechHMM in a file. +
  • FrameSelectorDataSet A dataset used to select some frames of another dataset. +
  • GaussianKernel Gaussian Kernel +
  • GradientMachine Gradient machine: machine which can be trained with a gradient descent. +
  • Grammar This class contains the grammar of accepted sentences for a speech recognition experiment such as the one using SimpleDecoderSpeechHMM A grammar is a transition table where each node is a word. +
  • HMM This class implements a Hidden Markov Model distribution. +
  • HTKDataSet This dataset can deal with the HTK format for features and targets. +
  • IOAscii Handles the standard Ascii sequence format in Torch. +
  • IOBin Handles the standard binary sequence format in Torch. +
  • IOBufferize This IO bufferizes the asked sequence of a given IO when calling getSequence(). +
  • IOHTK Handles the standard binary sequence format in HTK. +
  • IOHTKTarget Handles the standard Ascii HTK targets/labels format in Torch. +
  • IOMulti This IO takes several IOSequence, and will act as if you had concatened all these IOSequence when calling getMatrix(). +
  • IOSequence Class which provides an ensemble of sequences, which have the same frame size, but could have different number of frames. +
  • IOSequenceArray Load and save in an efficiently manner an array of sequences. +
  • IOSub IOSequence which does a selection of adjacent columns on another IOSequence, when calling getMatrix(). +
  • InputsSelect Machine which select a block of adjacent inputs, and put them in the outputs. +
  • IntCmdOption This class defines a integer command-line option. +
  • KFold Provides an interface to sample data, for use by methods such as cross-validation +
  • KMeans This class can be used to do a "kmeans" on a given set of data. +
  • KNN This machine implements the K-nearest-neighbors (KNN) algorithm. +
  • Kernel General Kernel class. +
  • LMCache This class implements a rudimentary caching scheme for language model lookup. +
  • LMCacheEntry This class implements the internal entries within the LMCache class. +
  • LMInteriorLevelWordEntry This class is used internally within the language model n-gram data structures. +
  • LMInteriorLevelWordList +
  • LMNGram This class is the main class for N-gram language modelling. +
  • LanguageModel This object implements an n-gram language model. +
  • LexiconInfo This class stores information about how phonemes are assembled into pronunciations. +
  • Linear Linear layer for GradientMachine. +
  • LinearLexicon This class is essentially an array of DecodingHMM instances, representing the HMM's for each pronunciation we can recognise. +
  • LogMixer LogMixer useful for experts mixtures. +
  • LogRBF LogRBF layer for GradientMachine. +
  • LogSigmoid Log-Sigmoid layer for GradientMachine. +
  • LogSoftMax Log-SoftMax layer for GradientMachine. +
  • MAPDiagonalGMM This class is a special case of a DiagonalGMM that implements the MAP algorithm instead of the EM algorithm. +
  • MAPHMM This class is a special case of a HMM that implements the MAP algorithm for HMM transitions probabilities. +
  • MLP A Multi-Layer Perceptron. +
  • MSECriterion Mean Squared Error criterion. +
  • MSEMeasurer Mean Squared Error measurer. +
  • Machine Object which can compute some outputs, given some inputs. +
  • Mat Matrix object. +
  • MatDataSet Matrix DataSet. +
  • MeanVarNorm In the constructor, it computes the mean and the standard deviation over all the frames in the given DataSet (by default, only for inputs). +
  • Measurer Used to measure what you want during training/testing. +
  • MemoryDataSet DataSet where data is fully loaded in memory. +
  • MemoryXFile A file in the memory. +
  • Mixer Mixer useful for experts mixtures. +
  • MultiClassFormat Define the multi class encoding format. +
  • MultiCriterion MultiCriterion can be used to handle multiple criterions. +
  • Multinomial This class can be used to model Multinomial Distributions. +
  • NLLCriterion This criterion can be used to train Distribution object using the GMTrainer trainer. +
  • NLLMeasurer This class measures the negative log likelihood. +
  • NPTrainer Trainer for Non Parametric Machines. +
  • NullXFile NullXFile. +
  • Object Almost all classes in Torch should be a sub-class of this class. +
  • OneHotClassFormat Define the one hot class encoding format. +
  • OutputMeasurer Compute the outputification error (in %) of the inputs with respect to the targets of data. +
  • Parameters Parameters definition. +
  • ParzenDistribution This class can be used to model a Parzen density estimator with a Gaussian kernel: +
  • ParzenMachine This machine implements the Parzen Window estimator. +
  • Perm Permutation object. +
  • PhoneInfo This class contains the names of the phonemes that make up the words in the lexicon. +
  • PhoneModels +
  • PipeXFile A file in a pipe. +
  • PolynomialKernel Polynomial Kernel . +
  • PreProcessing This class is able to do pre-processing on examples in a DataSet. +
  • QCCache "Cache" used by the Quadratic Constrained Trainer (QCTrainer). +
  • QCMachine "Quadratic Constrained Machine". +
  • QCTrainer Train a QCMachine. +
  • Random Random class which contains several static random methods. +
  • RealCmdOption This class defines a real command-line option. +
  • SVM Support Vector Machine. +
  • SVMCache QCCache implementation for SVMs. +
  • SVMCacheClassification Cache for SVM classification. +
  • SVMCacheRegression Cache for SVM regression. +
  • SVMClassification SVM in classification. +
  • SVMRegression SVM in regression. +
  • SaturationMeasurer Measure the saturation of a GradientMachine. +
  • Sequence Sequence definition. +
  • Sigmoid Sigmoid layer for GradientMachine. +
  • SigmoidKernel Sigmoid Kernel +
  • SimpleDecoderSpeechHMM This class implements a special case of Hidden Markov Models that can be used to do connected word speech recognition for small vocabulary, using embedded training. +
  • SoftMax SoftMax layer for GradientMachine. +
  • SoftPlus SoftPlus layer for GradientMachine. +
  • SpatialConvolution Class for doing convolution over images. +
  • SpatialSubSampling Class for doing sub-sampling over images. +
  • SpeechHMM This class implements a special case of Hidden Markov Models that can be used to do connected word speech recognition for small vocabulary, using embedded training. +
  • SpeechMLP +
  • SpeechMLPDistr +
  • Stack This is an implementation of a "stack". +
  • StochasticGradient Trainer for GradientMachine. +
  • StringCmdOption This class defines a string command-line option. +
  • SumMachine This machine simply adds up its input vectors. +
  • TableLookupDistribution This class outputs one of the observations as the logProbability. +
  • Tanh Tanh layer for GradientMachine. +
  • TemporalConvolution Class for doing a convolution over a sequence. +
  • TemporalMean Given an input sequence, it does the mean over all input frames. +
  • TemporalSubSampling Class for doing sub-sampling over a sequence. +
  • TimeMeasurer Measure the time (in seconds) between two measureIteration() calls. +
  • Timer Timer. +
  • Trainer Trainer. +
  • TwoClassFormat Define the two class encoding format. +
  • Vec Vector object. +
  • Vocabulary This object contains the list of words we want our recogniser to recognise plus a few "special" words (eg. +
  • WeightedMSECriterion Similar to MSECriterion, but you can put a weight on each example. +
  • WeightedSumMachine Weighted-sum machine. +
  • WordChainElemPool This class is a pool of pre-allocated WordChainElem structures. +
  • WordSeg This class keeps track of all information to compute word errors +
  • WordSegMeasurer This class can be used to save the word segmentation of a SimpleDecoderSpeechHMM in a file. +
  • XFile XFile. +
+

Macros

+
    +
  • max The max function +
  • min The min function +
+
Torch. +The Ultimate Machine Learning Library.
+
+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/logAdd.html b/torch3/manual/logAdd.html new file mode 100644 index 0000000..eba67c4a --- /dev/null +++ b/torch3/manual/logAdd.html @@ -0,0 +1,22 @@ + + + + + real Some simple functions for log operations.::logAdd + + + + +

real Some simple functions for log operations.::logAdd

(real log_a,
  real log_b)

logAdd(log_a,log_b) = log(a+b) = log(exp(log_a)+exp(log_b)) but done in a smart way so that if log_a or log_b are large but not their difference the computation works correctly
+ + +
+

Documentation

+
logAdd(log_a,log_b) = log(a+b) = log(exp(log_a)+exp(log_b)) +but done in a smart way so that if log_a or log_b are large +but not their difference the computation works correctly
+

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/logSub.html b/torch3/manual/logSub.html new file mode 100644 index 0000000..bba3c51 --- /dev/null +++ b/torch3/manual/logSub.html @@ -0,0 +1,20 @@ + + + + + real Some simple functions for log operations.::logSub + + + + +

real Some simple functions for log operations.::logSub

(real log_a,
  real log_b)

logSub(log_a,log_b) = log(a-b)
+ + +
+

Documentation

+
logSub(log_a,log_b) = log(a-b)
+

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/logo.gif b/torch3/manual/logo.gif new file mode 100644 index 0000000000000000000000000000000000000000..3b7913677dc1430db087939c96ccbbd7939bf7a8 GIT binary patch literal 2961 zcmbu6iC5EC7RP_T>>FtkLrf4$f-DgX21HD8`z7o&*dU0Y;3O!!OQ5J|QIe1VQc4jJ zIaVNm3o0VefQrfq2#Vm6L3E&68*roOC{PSc#=cJaH_Scnyz{x=_r3SNb8bjju;?qr zCMX2D13@3CR7(}h(!v5@*wV!Spw@baVI8IdaM=3PcJHvhpnhOct#51`{=tu7{a^#X z*w0ATx175H1c2!O^?>Hxq)0FteLkMjZGDF7QR&UM zAQ1qob=YR}2f)iZYwI%$z)=8fhHU_x0-zXxasXNYm;j*5I%P970B`_+%>dj1AQ%8Q z0QUa%{{;`&2V^BFvXgdk52j_Oa-&m|xFKN?GKlvd3`~OZpcRlU{$3V@2dX?xzE)RI zSQs7YwVFxVdKrwyp(%Gh8G>3i~R5ywzKD?XOQQbM&9zV z3qJ0@4P9l4{5*VxZ{EF|s%COTN^FU2leGWF$g2t+&Y$Y2_eR~Zqd1|M(S;v)L^Li!gN zsQf0MjEr%p;HS`vFB4MGBgYrld2r3*{zB&RF5JD)$Y5B*BfSipDG!Jfkaq_6{fUqI zKypBWj!fuRU})~*N@?6XuLyF}5(Cohfa+CTDZ(cz7bj9mM<49{ii~v`kT9Zlt)(c$ z$i(%jz}TiONjf50)a(~(GQi{>x%8+AD?c}?%~{g zttd=T8=jEZBf&<0)McY>`=Lk_BI*TDF={NfzAnJS@#JXYj>}xscHdD9mdS*sRrtW` zotgwr{Bb*CGUWY2ATmvx<3$BmQAfNnlj`^!YW8a~C;nephx?i5Z`%b$601lYDGj~Z zZ%o?=;hXw*eG`7oto^Q^-nvBUl=?o$XpUYRmP_3iUbqI+uz z;!^ApIfQ8`(D#!346k(;PpQp)IkCUeQs{3-pHxxTu;|d0jM)?kdXR!Na}yn3%J^%c zg~-U81=BlE!-k}92t*87+u3)ZwQlX&(?j(k_>z>~X3t#H=&6j0C&a90{K=eGBC=B=1HW``OWJkdBMrzPTOd{-3g{r(!2!oGrC+2-}U z!a-HU5vCy?~wjBXz^wG)d8|^qE4&wrK7% zl#|L3&kt0tBM`O=Q+lZToS$|ExMPlwImtyt5{AU$8QoV7a1W7My3p!d{(r>o*T+=y zg4uaz%wYt7r9pzKkKJ0&7U%Nr+}C^-9!4!2S zZ-x7Z+o+4?5a!C9VoE`oH+jx{=-p4-8Y`EPmY>#O9T)oGn1Hfxo4L40_f(7grVG8A zJTa2(c8xd&grXsk6JgQThnZ!aQrMm#{~Db*3$tlv+yn`Ul9c6d%uz5!vL*M*XHU$l zQBLGZ*e)E(XOx(so9%=4u}YH1NQ&0U1h0~)boA_3=mG!R90c^#U~Z;GE#VR1=V
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#define max

(a, b)

The max function
+ + +
+

Documentation

+
The max function
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/message.html b/torch3/manual/message.html new file mode 100644 index 0000000..7236071 --- /dev/null +++ b/torch3/manual/message.html @@ -0,0 +1,20 @@ + + + + + void message + + + + +

void message

(const char* msg, ...)

Print a message
+ + +
+

Documentation

+
Print a message
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/min.html b/torch3/manual/min.html new file mode 100644 index 0000000..769477d --- /dev/null +++ b/torch3/manual/min.html @@ -0,0 +1,20 @@ + + + + + #define min + + + + +

#define min

(a, b)

The min function
+ + +
+

Documentation

+
The min function
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxHFactor.html b/torch3/manual/mxHFactor.html new file mode 100644 index 0000000..cf298d7 --- /dev/null +++ b/torch3/manual/mxHFactor.html @@ -0,0 +1,21 @@ + + + + + void Routines for determining Hessenberg factorisations.::mxHFactor + + + + +

void Routines for determining Hessenberg factorisations.::mxHFactor

(Mat* mat,
  Vec* diag,
  Vec* beta)

Compute Hessenberg factorisation in compact form.
+ + +
+

Documentation

+
Compute Hessenberg factorisation in compact form. +Factorisation performed in situ.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxHhTrRows.html b/torch3/manual/mxHhTrRows.html new file mode 100644 index 0000000..caf70d2 --- /dev/null +++ b/torch3/manual/mxHhTrRows.html @@ -0,0 +1,21 @@ + + + + + void Householder transformation routines.::mxHhTrRows + + + + +

void Householder transformation routines.::mxHhTrRows

(Mat* mat,
  int i0,
  int j0,
  Vec* hh,
  real beta)

Transform a matrix by a Householder vector by rows.
+ + +
+

Documentation

+
Transform a matrix by a Householder vector by rows. +Start at row i0 from column j0. In-situ.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxHhTrVec.html b/torch3/manual/mxHhTrVec.html new file mode 100644 index 0000000..f7d4eb4 --- /dev/null +++ b/torch3/manual/mxHhTrVec.html @@ -0,0 +1,21 @@ + + + + + void Householder transformation routines.::mxHhTrVec + + + + +

void Householder transformation routines.::mxHhTrVec

(Vec* hh,
  real beta,
  int i0,
  Vec* in,
  Vec* out)

Apply Householder transformation to vector.
+ + +
+

Documentation

+
Apply Householder transformation to vector. +May be in-situ. (hh is the Householder vector).
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxHhVec.html b/torch3/manual/mxHhVec.html new file mode 100644 index 0000000..0a1fe33 --- /dev/null +++ b/torch3/manual/mxHhVec.html @@ -0,0 +1,22 @@ + + + + + void Householder transformation routines.::mxHhVec + + + + +

void Householder transformation routines.::mxHhVec

(Vec* vec,
  int i0,
  real* beta,
  Vec* out,
  real* newval)

Calulates Householder vector.
+ + +
+

Documentation

+
Calulates Householder vector. +To eliminate all entries after the i0 entry of the vector vec. +It is returned as out. May be in-situ.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxInverse.html b/torch3/manual/mxInverse.html new file mode 100644 index 0000000..012b82d --- /dev/null +++ b/torch3/manual/mxInverse.html @@ -0,0 +1,22 @@ + + + + + void Collection of matrix factorisation operation functions.::mxInverse + + + + +

void Collection of matrix factorisation operation functions.::mxInverse

(Mat* mat,
  Mat* out)

Returns inverse of A, provided A is not too rank deficient.
+ + +
+

Documentation

+
+Returns inverse of A, provided A is not too rank deficient. +Uses LU factorisation.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxLUFactor.html b/torch3/manual/mxLUFactor.html new file mode 100644 index 0000000..dab1dce --- /dev/null +++ b/torch3/manual/mxLUFactor.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix factorisation operation functions.::mxLUFactor + + + + +

void Collection of matrix factorisation operation functions.::mxLUFactor

(Mat* mat,
  Perm* pivot)

Gaussian elimination with scaled partial pivoting.
+ + +
+

Documentation

+
Gaussian elimination with scaled partial pivoting. +-- Note: returns LU matrix which is A.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxLUSolve.html b/torch3/manual/mxLUSolve.html new file mode 100644 index 0000000..e0df330 --- /dev/null +++ b/torch3/manual/mxLUSolve.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix factorisation operation functions.::mxLUSolve + + + + +

void Collection of matrix factorisation operation functions.::mxLUSolve

(Mat* mat,
  Perm* pivot,
  Vec* b,
  Vec* x)

Given an LU factorisation in A, solve Ax=b
+ + +
+

Documentation

+
+Given an LU factorisation in A, solve Ax=b
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxLUTSolve.html b/torch3/manual/mxLUTSolve.html new file mode 100644 index 0000000..022f4e7 --- /dev/null +++ b/torch3/manual/mxLUTSolve.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix factorisation operation functions.::mxLUTSolve + + + + +

void Collection of matrix factorisation operation functions.::mxLUTSolve

(Mat* mat,
  Perm* pivot,
  Vec* b,
  Vec* x)

Given an LU factorisation in A, solve A^Tx=b
+ + +
+

Documentation

+
+Given an LU factorisation in A, solve A^Tx=b
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMakeH.html b/torch3/manual/mxMakeH.html new file mode 100644 index 0000000..84b20c7 --- /dev/null +++ b/torch3/manual/mxMakeH.html @@ -0,0 +1,20 @@ + + + + + void Routines for determining Hessenberg factorisations.::mxMakeH + + + + +

void Routines for determining Hessenberg factorisations.::mxMakeH

(Mat* h_mat,
  Mat* h_out)

Construct actual Hessenberg matrix
+ + +
+

Documentation

+
Construct actual Hessenberg matrix
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMakeHQ.html b/torch3/manual/mxMakeHQ.html new file mode 100644 index 0000000..0aa99e9 --- /dev/null +++ b/torch3/manual/mxMakeHQ.html @@ -0,0 +1,21 @@ + + + + + void Routines for determining Hessenberg factorisations.::mxMakeHQ + + + + +

void Routines for determining Hessenberg factorisations.::mxMakeHQ

(Mat* h_mat,
  Vec* diag,
  Vec* beta,
  Mat* q_out)

Construct the Hessenberg orthogonalising matrix Q.
+ + +
+

Documentation

+
Construct the Hessenberg orthogonalising matrix Q. +i.e. Hess M = Q.M.Q'.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatAddMat.html b/torch3/manual/mxMatAddMat.html new file mode 100644 index 0000000..abed482 --- /dev/null +++ b/torch3/manual/mxMatAddMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of matrix operation functions.::mxMatAddMat + + + + +

void Collection of matrix operation functions.::mxMatAddMat

(Mat* mat1,
  Mat* mat2,
  Mat* out)

Matrix addition -- may be in-situ
+ + +
+

Documentation

+
Matrix addition -- may be in-situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatAddRealMulMat.html b/torch3/manual/mxMatAddRealMulMat.html new file mode 100644 index 0000000..fa4e0a2 --- /dev/null +++ b/torch3/manual/mxMatAddRealMulMat.html @@ -0,0 +1,22 @@ + + + + + void Collection of matrix operation functions.::mxMatAddRealMulMat + + + + +

void Collection of matrix operation functions.::mxMatAddRealMulMat

(Mat* mat1,
  Mat* mat2,
  real s,
  Mat* out)

Matrix-scalar multiply and add.
+ + +
+

Documentation

+
Matrix-scalar multiply and add. +-- may be in situ. +-- returns out == A1 + s*A2
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatMulMat.html b/torch3/manual/mxMatMulMat.html new file mode 100644 index 0000000..baed219 --- /dev/null +++ b/torch3/manual/mxMatMulMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of matrix operation functions.::mxMatMulMat + + + + +

void Collection of matrix operation functions.::mxMatMulMat

(Mat* mat1,
  Mat* mat2,
  Mat* out)

Matrix-matrix multiplication
+ + +
+

Documentation

+
Matrix-matrix multiplication
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatMulTrMat.html b/torch3/manual/mxMatMulTrMat.html new file mode 100644 index 0000000..fbbfa67 --- /dev/null +++ b/torch3/manual/mxMatMulTrMat.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxMatMulTrMat + + + + +

void Collection of matrix operation functions.::mxMatMulTrMat

(Mat* mat1,
  Mat* mat2,
  Mat* out)

Matrix-matrix transposed multiplication.
+ + +
+

Documentation

+
Matrix-matrix transposed multiplication. +-- A.B^T is stored in out
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatMulVec.html b/torch3/manual/mxMatMulVec.html new file mode 100644 index 0000000..6a4a738 --- /dev/null +++ b/torch3/manual/mxMatMulVec.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxMatMulVec + + + + +

void Collection of matrix operation functions.::mxMatMulVec

(Mat* mat,
  Vec* b,
  Vec* out)

Matrix-vector multiplication.
+ + +
+

Documentation

+
Matrix-vector multiplication. +-- Note: b is treated as a column vector
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxMatSubMat.html b/torch3/manual/mxMatSubMat.html new file mode 100644 index 0000000..1e9bb3d --- /dev/null +++ b/torch3/manual/mxMatSubMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of matrix operation functions.::mxMatSubMat + + + + +

void Collection of matrix operation functions.::mxMatSubMat

(Mat* mat1,
  Mat* mat2,
  Mat* out)

Matrix subtraction -- may be in-situ
+ + +
+

Documentation

+
Matrix subtraction -- may be in-situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermColsMat.html b/torch3/manual/mxPermColsMat.html new file mode 100644 index 0000000..128847e --- /dev/null +++ b/torch3/manual/mxPermColsMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of permutations operation functions.::mxPermColsMat + + + + +

void Collection of permutations operation functions.::mxPermColsMat

(Perm* px,
  Mat* mat,
  Mat* out)

Permute columns of matrix A; out = Apx'.
+ + +
+

Documentation

+
Permute columns of matrix A; out = Apx'. -- May NOT be in situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermInv.html b/torch3/manual/mxPermInv.html new file mode 100644 index 0000000..821447c --- /dev/null +++ b/torch3/manual/mxPermInv.html @@ -0,0 +1,21 @@ + + + + + void Collection of permutations operation functions.::mxPermInv + + + + +

void Collection of permutations operation functions.::mxPermInv

(Perm* px,
  Perm* out)

Invert permutation -- in situ.
+ + +
+

Documentation

+
Invert permutation -- in situ. +Taken from ACM Collected Algorithms 250.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermInvVec.html b/torch3/manual/mxPermInvVec.html new file mode 100644 index 0000000..8b7a1ba --- /dev/null +++ b/torch3/manual/mxPermInvVec.html @@ -0,0 +1,21 @@ + + + + + void Collection of permutations operation functions.::mxPermInvVec + + + + +

void Collection of permutations operation functions.::mxPermInvVec

(Perm* px,
  Vec* x,
  Vec* out)

Apply the inverse of px to x, returning the result in out.
+ + +
+

Documentation

+
Apply the inverse of px to x, returning the result in out. +Can be in-situ, but "oh booooy!"...
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermMulPerm.html b/torch3/manual/mxPermMulPerm.html new file mode 100644 index 0000000..a7a90d8 --- /dev/null +++ b/torch3/manual/mxPermMulPerm.html @@ -0,0 +1,20 @@ + + + + + void Collection of permutations operation functions.::mxPermMulPerm + + + + +

void Collection of permutations operation functions.::mxPermMulPerm

(Perm* px1,
  Perm* px2,
  Perm* out)

Permutation multiplication (composition) -- not in-situ
+ + +
+

Documentation

+
Permutation multiplication (composition) -- not in-situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermRowsMat.html b/torch3/manual/mxPermRowsMat.html new file mode 100644 index 0000000..59380bc --- /dev/null +++ b/torch3/manual/mxPermRowsMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of permutations operation functions.::mxPermRowsMat + + + + +

void Collection of permutations operation functions.::mxPermRowsMat

(Perm* px,
  Mat* mat,
  Mat* out)

Permute rows of matrix A; out = pxA.
+ + +
+

Documentation

+
Permute rows of matrix A; out = pxA. -- May NOT be in situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxPermVec.html b/torch3/manual/mxPermVec.html new file mode 100644 index 0000000..a3f459c --- /dev/null +++ b/torch3/manual/mxPermVec.html @@ -0,0 +1,20 @@ + + + + + void Collection of permutations operation functions.::mxPermVec + + + + +

void Collection of permutations operation functions.::mxPermVec

(Perm* px,
  Vec* vec,
  Vec* out)

Permute vector -- can be in-situ
+ + +
+

Documentation

+
Permute vector -- can be in-situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxRealMulMat.html b/torch3/manual/mxRealMulMat.html new file mode 100644 index 0000000..872ec9f --- /dev/null +++ b/torch3/manual/mxRealMulMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of matrix operation functions.::mxRealMulMat + + + + +

void Collection of matrix operation functions.::mxRealMulMat

(real scalar,
  Mat* matrix,
  Mat* out)

Scalar-matrix multiply -- may be in-situ
+ + +
+

Documentation

+
Scalar-matrix multiply -- may be in-situ
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxSolve.html b/torch3/manual/mxSolve.html new file mode 100644 index 0000000..8390afa --- /dev/null +++ b/torch3/manual/mxSolve.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix factorisation operation functions.::mxSolve + + + + +

void Collection of matrix factorisation operation functions.::mxSolve

(Mat* mat,
  Vec* b,
  Vec* x)

Given A and b, solve Ax=b
+ + +
+

Documentation

+
+Given A and b, solve Ax=b
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxSwapColsMat.html b/torch3/manual/mxSwapColsMat.html new file mode 100644 index 0000000..1fd855d --- /dev/null +++ b/torch3/manual/mxSwapColsMat.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxSwapColsMat + + + + +

void Collection of matrix operation functions.::mxSwapColsMat

(Mat* mat,
  int i,
  int j,
  int lo,
  int hi)

Swap columns i and j of matrix A upto row lim.
+ + +
+

Documentation

+
Swap columns i and j of matrix A upto row lim. +lo and hi to -1 if you want to swap all
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxSwapRowsMat.html b/torch3/manual/mxSwapRowsMat.html new file mode 100644 index 0000000..c31b755 --- /dev/null +++ b/torch3/manual/mxSwapRowsMat.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxSwapRowsMat + + + + +

void Collection of matrix operation functions.::mxSwapRowsMat

(Mat* mat,
  int i,
  int j,
  int lo,
  int hi)

Swaps rows i and j of matrix A upto column lim.
+ + +
+

Documentation

+
Swaps rows i and j of matrix A upto column lim. +lo and hi to -1 if you want to swap all
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxSymEig.html b/torch3/manual/mxSymEig.html new file mode 100644 index 0000000..cade556 --- /dev/null +++ b/torch3/manual/mxSymEig.html @@ -0,0 +1,23 @@ + + + + + void Routines for symmetric eigenvalue problems.::mxSymEig + + + + +

void Routines for symmetric eigenvalue problems.::mxSymEig

(Mat* mat_a,
  Mat* mat_q,
  Vec* out)

Computes eigenvalues of a dense symmetric matrix.
+ + +
+

Documentation

+
Computes eigenvalues of a dense symmetric matrix. +mat_a must be symmetric on entry. +Eigenvalues stored in out. +mat_q contains orthogonal matrix of eigenvectors if not NULL.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxTrMat.html b/torch3/manual/mxTrMat.html new file mode 100644 index 0000000..39757a3 --- /dev/null +++ b/torch3/manual/mxTrMat.html @@ -0,0 +1,20 @@ + + + + + void Collection of matrix operation functions.::mxTrMat + + + + +

void Collection of matrix operation functions.::mxTrMat

(Mat* in,
  Mat* out)

Transpose matrix
+ + +
+

Documentation

+
Transpose matrix
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxTrMatMulMat.html b/torch3/manual/mxTrMatMulMat.html new file mode 100644 index 0000000..5bfc685 --- /dev/null +++ b/torch3/manual/mxTrMatMulMat.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxTrMatMulMat + + + + +

void Collection of matrix operation functions.::mxTrMatMulMat

(Mat* mat1,
  Mat* mat2,
  Mat* out)

Matrix transposed-matrix multiplication.
+ + +
+

Documentation

+
Matrix transposed-matrix multiplication. +-- A^T.B is stored in out
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxTrPerm.html b/torch3/manual/mxTrPerm.html new file mode 100644 index 0000000..cdd61dc --- /dev/null +++ b/torch3/manual/mxTrPerm.html @@ -0,0 +1,22 @@ + + + + + void Collection of permutations operation functions.::mxTrPerm + + + + +

void Collection of permutations operation functions.::mxTrPerm

(Perm* px,
  int i1,
  int i2)

Transpose elements of permutation.
+ + +
+

Documentation

+
Transpose elements of permutation. +Really multiplying a permutation by a transposition. +i1 and i2 are the elements to transpose.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxTriEig.html b/torch3/manual/mxTriEig.html new file mode 100644 index 0000000..5253010 --- /dev/null +++ b/torch3/manual/mxTriEig.html @@ -0,0 +1,24 @@ + + + + + void Routines for symmetric eigenvalue problems.::mxTriEig + + + + +

void Routines for symmetric eigenvalue problems.::mxTriEig

(Vec* a,
  Vec* b,
  Mat* mat_q)

Finds eigenvalues of symmetric tridiagonal matrices.
+ + +
+

Documentation

+
Finds eigenvalues of symmetric tridiagonal matrices. +The matrix is represented by a pair of vectors a (diag entries) +and b (sub-diag and super-diag entries). +Eigenvalues in a on return, and eigenvectors in mat_q, if this one +is not NULL.
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxVecAddRealMulMatMulVec.html b/torch3/manual/mxVecAddRealMulMatMulVec.html new file mode 100644 index 0000000..1576f71 --- /dev/null +++ b/torch3/manual/mxVecAddRealMulMatMulVec.html @@ -0,0 +1,22 @@ + + + + + void Collection of matrix operation functions.::mxVecAddRealMulMatMulVec + + + + +

void Collection of matrix operation functions.::mxVecAddRealMulMatMulVec

(Vec* v1,
  real alpha,
  Mat* mat,
  Vec* v2,
  Vec* out)

Matrix-vector multiply and add.
+ + +
+

Documentation

+
Matrix-vector multiply and add. +-- may not be in situ +-- returns out == v1 + alpha*A*v2
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxVecAddRealMulVecMulMat.html b/torch3/manual/mxVecAddRealMulVecMulMat.html new file mode 100644 index 0000000..694cc9c --- /dev/null +++ b/torch3/manual/mxVecAddRealMulVecMulMat.html @@ -0,0 +1,22 @@ + + + + + void Collection of matrix operation functions.::mxVecAddRealMulVecMulMat + + + + +

void Collection of matrix operation functions.::mxVecAddRealMulVecMulMat

(Vec* v1,
  real alpha,
  Vec* v2,
  Mat* mat,
  Vec* out)

Vector-matrix multiply and add -- may not be in situ -- returns out' == v1' + alpha * v2'*A
+ + +
+

Documentation

+
Vector-matrix multiply and add +-- may not be in situ +-- returns out' == v1' + alpha * v2'*A
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mxVecMulMat.html b/torch3/manual/mxVecMulMat.html new file mode 100644 index 0000000..d57482f --- /dev/null +++ b/torch3/manual/mxVecMulMat.html @@ -0,0 +1,21 @@ + + + + + void Collection of matrix operation functions.::mxVecMulMat + + + + +

void Collection of matrix operation functions.::mxVecMulMat

(Vec* b,
  Mat* mat,
  Vec* out)

Vector-matrix multiplication.
+ + +
+

Documentation

+
Vector-matrix multiplication. +-- Note: b is treated as a row vector
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mx_givens.html b/torch3/manual/mx_givens.html new file mode 100644 index 0000000..5d2eaec --- /dev/null +++ b/torch3/manual/mx_givens.html @@ -0,0 +1,21 @@ + + + + + void Givens matrix operations routines.::mx_givens + + + + +

void Givens matrix operations routines.::mx_givens

(real x,
  real y,
  real* c,
  real* s)

Returns c, s parameters for Givens rotation to eliminate y in the vector [ x y ]'
+ + +
+

Documentation

+
Returns c, s parameters for Givens rotation +to eliminate y in the vector [ x y ]'
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mx_rot_cols.html b/torch3/manual/mx_rot_cols.html new file mode 100644 index 0000000..353033b --- /dev/null +++ b/torch3/manual/mx_rot_cols.html @@ -0,0 +1,20 @@ + + + + + void Givens matrix operations routines.::mx_rot_cols + + + + +

void Givens matrix operations routines.::mx_rot_cols

(Mat* mat,
  int i,
  int k,
  real c,
  real s,
  Mat* out)

Postmultiply mat by givens rotation described by c,s
+ + +
+

Documentation

+
Postmultiply mat by givens rotation described by c,s
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mx_rot_rows.html b/torch3/manual/mx_rot_rows.html new file mode 100644 index 0000000..c154e6c --- /dev/null +++ b/torch3/manual/mx_rot_rows.html @@ -0,0 +1,20 @@ + + + + + void Givens matrix operations routines.::mx_rot_rows + + + + +

void Givens matrix operations routines.::mx_rot_rows

(Mat* mat,
  int i,
  int k,
  real c,
  real s,
  Mat* out)

Premultiply mat by givens rotation described by c,s
+ + +
+

Documentation

+
Premultiply mat by givens rotation described by c,s
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/mx_rot_vec.html b/torch3/manual/mx_rot_vec.html new file mode 100644 index 0000000..51b763b --- /dev/null +++ b/torch3/manual/mx_rot_vec.html @@ -0,0 +1,20 @@ + + + + + void Givens matrix operations routines.::mx_rot_vec + + + + +

void Givens matrix operations routines.::mx_rot_vec

(Vec* x,
  int i,
  int k,
  real c,
  real s,
  Vec* out)

Apply Givens rotation to x's i and k components
+ + +
+

Documentation

+
Apply Givens rotation to x's i and k components
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/print.html b/torch3/manual/print.html new file mode 100644 index 0000000..90c18ac --- /dev/null +++ b/torch3/manual/print.html @@ -0,0 +1,20 @@ + + + + + void print + + + + +

void print

(const char* msg, ...)

Like printf
+ + +
+

Documentation

+
Like printf
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/strBaseName.html b/torch3/manual/strBaseName.html new file mode 100644 index 0000000..b99447d --- /dev/null +++ b/torch3/manual/strBaseName.html @@ -0,0 +1,21 @@ + + + + + char* Some simple functions for string operations.::strBaseName + + + + +

char* Some simple functions for string operations.::strBaseName

(char* filename)

Returns the name of a file without leading pathname.
+ + +
+

Documentation

+
Returns the name of a file without leading pathname. +(It's not a new string, but a pointer in the given string)
+

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+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/strConcat.html b/torch3/manual/strConcat.html new file mode 100644 index 0000000..cacddf4 --- /dev/null +++ b/torch3/manual/strConcat.html @@ -0,0 +1,22 @@ + + + + + char* Some simple functions for string operations.::strConcat + + + + +

char* Some simple functions for string operations.::strConcat

(int n,
  ...)

Returns the concatenation n strings.
+ + +
+

Documentation

+
Returns the concatenation n strings. +The strings are the parameters given after n; +You have to free the memory!
+

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/strRemoveSuffix.html b/torch3/manual/strRemoveSuffix.html new file mode 100644 index 0000000..a9bf52e --- /dev/null +++ b/torch3/manual/strRemoveSuffix.html @@ -0,0 +1,21 @@ + + + + + char* Some simple functions for string operations.::strRemoveSuffix + + + + +

char* Some simple functions for string operations.::strRemoveSuffix

(char* filename,
  char c='.')

Returns a fresh copy of the name of a file without suffix.
+ + +
+

Documentation

+
Returns a fresh copy of the name of a file without suffix. +(Trailing chars after c) You have to free the memory!
+

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/manual/warning.html b/torch3/manual/warning.html new file mode 100644 index 0000000..573a49c --- /dev/null +++ b/torch3/manual/warning.html @@ -0,0 +1,20 @@ + + + + + void warning + + + + +

void warning

(const char* msg, ...)

Print a warning message
+ + +
+

Documentation

+
Print a warning message
+

Alphabetic index HTML hierarchy of classes or Java


+
+This page was generated with the help of DOC++. + + diff --git a/torch3/matos/convolutions.pdf b/torch3/matos/convolutions.pdf new file mode 100644 index 0000000000000000000000000000000000000000..0ae1a21f28985b4019cdec0edb546fe3cd5ff36d GIT binary patch literal 203562 zcmeFa2V7J;6E|!xYwryeyP~pe-&O1af+$Ewuq?0$NG}TZj@JVA-g~d8c*Wj(7gSUf zz4qS4^8P0|3kUJu%e~L@{l4%0evi1>Y))p9Oft!2CX>_1v9oncnYmn|F|{xa^9hnz zT1uoYap4B3Rj6;6UtnlIiL`T|zrP{U5bA4)@=_?IhFITVeTXz7CM??E=Mx+m*e@Vj z8X6PgV~C6j>=!Ea3kwd`M@qvDk-mn|XsJE~u_%40ABW)C!}Y)yZ19hkvKUX)M@1VV z1Ecy&!-Hd@q`qMxA$n;*TzG&Xl#m66`AMUK^-%%RL59dMX;`R18a*&f8XXX6Fi8Ew zVj`vffddTEsK8ihlwkm147_52$mkmu92Sb?kU$>eP4EjFh+Gjd`e0Pe5EUI57Rr*0 zKcxC-X$NUXX(wrCsg=}PY9s9;wUydQyGre)-K5>64pK*H52=&XS?VHnmAXmYr5;jG zX-}z7q~5o`A(}PMNG0||c)(lh8yM*u6XG9ihy}%>^}dW)EIZ4qm-+L_bCaMoDe-MBL7X;Ap+nCBT5tULWG)rlfaYKVWH6ysdJ1^G;t`gsZ1j6 zt`9Lttr4N8oefdGk%8gSVUeaf4%ks2WuPb0uAQAbIdo{=shg8bgUo@EQPG_O^pU0t zg#^7X{E+F?5~+KjUvxl}mt3hcSDPwTT7(*n++3C`u94}?wWd6eLZ!r09t!!zPc3BT 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