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Refine mxnet python installation #12696
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@mxnet-label-bot[pr-awaiting-review] |
|
@aaronmarkham for review |
ankkhedia
reviewed
Sep 30, 2018
docs/install/windows_setup.md
Outdated
| @@ -221,9 +222,6 @@ libgfortran-3.dll (in mingw64_dll) | |||
| libquadmath-0.dll (in mingw64_dll) | |||
| libopenblas.dll (in OpenBlas folder you download) | |||
| opencv_world341.dll (in OpenCV folder you download) | |||
| kernel32.dll | |||
| vcomp140.dll | |||
| nvcuda.dll (only if you use CUDA) | |||
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Why do we remove these dlls?
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They are under C:Windows\System32 where python would check during loading libmxnet.dll
| @@ -141,10 +141,10 @@ To build and install MXNet yourself using [VS2017](https://www.visualstudio.com/ | |||
| 1. Set the environment variable `OpenCV_DIR` to point to the OpenCV build directory that you just unzipped. Start ```cmd``` and type `set OpenCV_DIR=C:\utils\opencv\build`. | |||
| 1. If you don’t have the Intel Math Kernel Library (MKL) installed, you can install it and follow the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md) from here, or you can use OpenBLAS. These instructions will assume you're using OpenBLAS. | |||
| 1. Download the [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.19/OpenBLAS-v0.2.19-Win64-int32.zip/download) package. Later versions of OpenBLAS are available, but you would need to build from source. v0.2.19 is the most recent version that ships with binaries. Contributions of more recent binaries would be appreciated. | |||
| 1. Unzip the file. You can place the unzipped files and folders in another directory if you wish. | |||
| 1. Unzip the file, rename it to ```OpenBLAS``` and put it under `C:\utils`. You can place the unzipped files and folders in another directory if you wish. | |||
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories and type `set OpenBLAS_HOME=C:\utils\OpenBLAS` on the command prompt(```cmd```). | |||
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Since the file can be unzipped and placed anywhere, what is significance of C:\utils
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Yeah, it could be anywhere but original tutorial use C"\utils so I follow it. It makes users less confused?
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Usually environment variables are all caps. why is it OpenBLAS_HOME?
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not sure why OpenBLAS_HOME and OpenCV_DIR environment variables are not all cps
aaronmarkham
suggested changes
Oct 1, 2018
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What I'm seeing is that we need two sets of directions.
- Using OpenBLAS
- Using MKL or MKL-DNN
Changing the general directions and build settings to disable MKL isn't really going to help the user when they could get a better build from MKL or MKL-DNN when on Intel hardware.
Also, I think this PR is more about dependencies for Python binding rather that instructions on how to install the binding itself, correct? Might update the PR summary to describe the kinds of changes you're going for... and why. This helps troubleshoot since it seems you've found some issues that this PR will help avoid.
| 1. If you don’t have the Intel Math Kernel Library (MKL) installed, you can install it and follow the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md) from here, or you can use OpenBLAS. These instructions will assume you're using OpenBLAS. | ||
| 1. Download the [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.19/OpenBLAS-v0.2.19-Win64-int32.zip/download) package. Later versions of OpenBLAS are available, but you would need to build from source. v0.2.19 is the most recent version that ships with binaries. Contributions of more recent binaries would be appreciated. | ||
| 1. Unzip the file. You can place the unzipped files and folders in another directory if you wish. | ||
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories (e.g., `OpenBLAS_HOME = C:\utils\OpenBLAS`). | ||
| 1. Download and install [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal). If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. |
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Why why is this new order of operations for CUDA and cuDNN?
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I think the order is still OpenBLAS -> CUDA -> cuDNN. Did you mean that?
docs/install/windows_setup.md
Outdated
| ``` | ||
| 5. Compile the MXNet source code with `cmake` by using following command: | ||
| ``` | ||
| cmake -G "Visual Studio 15 2017 Win64" -T cuda=9.2,host=x64 -DUSE_CUDA=1 -DUSE_CUDNN=1 -DUSE_NVRTC=1 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_BLAS=open -DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_LIST=Common -DCUDA_TOOLSET=9.2 -DCUDNN_INCLUDE=C:\cuda\include -DCUDNN_LIBRARY=C:\cuda\lib\x64\cudnn.lib "C:\incubator-mxnet" | ||
| cmake -G "Visual Studio 15 2017 Win64" -T cuda=9.2,host=x64 -DUSE_CUDA=1 -DUSE_CUDNN=1 -DUSE_NVRTC=1 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_BLAS=open -DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DUSE_MKL_IF_AVAILABLE=OFF -DCUDA_ARCH_LIST=Common -DCUDA_TOOLSET=9.2 -DCUDNN_INCLUDE=C:\cuda\include -DCUDNN_LIBRARY=C:\cuda\lib\x64\cudnn.lib "C:\incubator-mxnet" |
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What's going on here? What does turning off MKL have to do with setting up the Python binding? I believe the idea is that you can opportunistically use MKL or MKL-DNN. Otherwise, use OpenBLAS.
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I will remove -DUSE_MKL_IF_AVAILABLE=OFF. The user should be allowed to use OpenBLAS, MKL, or MKL-DNN
docs/install/windows_setup.md
Outdated
| * Select the **Advanced tab** and click **Environment Variables** | ||
| * Double click the **Path** and click **New** | ||
| * Add ```C:\common``` and click OK | ||
| 7. Next, we install Python package interface for MXNet. You can find the Python interface package for [MXNet on GitHub](https://github.com/dmlc/mxnet/tree/master/python/mxnet). |
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There's a section on the page that tells the user what to do next for the Python bindings. Lead them to that!
https://mxnet.incubator.apache.org/install/windows_setup.html#install-mxnet-for-python
Also, I see that the anchor was changed so that the Table of Contents link to the Python section is broken (likely my fault). Please update that since you're already updating this file. https://github.com/apache/incubator-mxnet/blame/master/docs/install/windows_setup.md#L13
stu1130
commented
Oct 1, 2018
| 1. If you don’t have the Intel Math Kernel Library (MKL) installed, you can install it and follow the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md) from here, or you can use OpenBLAS. These instructions will assume you're using OpenBLAS. | ||
| 1. Download the [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.19/OpenBLAS-v0.2.19-Win64-int32.zip/download) package. Later versions of OpenBLAS are available, but you would need to build from source. v0.2.19 is the most recent version that ships with binaries. Contributions of more recent binaries would be appreciated. | ||
| 1. Unzip the file. You can place the unzipped files and folders in another directory if you wish. | ||
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories (e.g., `OpenBLAS_HOME = C:\utils\OpenBLAS`). | ||
| 1. Download and install [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal). If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. |
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I think the order is still OpenBLAS -> CUDA -> cuDNN. Did you mean that?
|
@aaronmarkham let me know if you have any question |
aaronmarkham
reviewed
Oct 2, 2018
docs/install/windows_setup.md
Outdated
| * Select the **Advanced tab** and click **Environment Variables** | ||
| * Double click the **Path** and click **New** | ||
| * Add ```C:\common``` and click OK | ||
| 7. Finally, we install Python package interface for MXNet. You can find the Python interface package for [MXNet on GitHub](https://github.com/dmlc/mxnet/tree/master/python/mxnet). |
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I don't think you need this... just let the user continue on with running setup.py...
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How about putting these in a faq or reminder? I used OpenBLAS and was struggling to install python due to lack of those .dll files.
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I'm specifically talking about the link that goes to the old repo. Not only is that not the right link, I don't think users need step 7 at all.
aaronmarkham
reviewed
Oct 2, 2018
docs/install/windows_setup.md
Outdated
| @@ -228,7 +228,7 @@ opencv_world341.dll (in OpenCV folder you download) | |||
| * Select the **Advanced tab** and click **Environment Variables** | |||
| * Double click the **Path** and click **New** | |||
| * Add ```C:\common``` and click OK | |||
| 7. Use setup.py to insatll the package | |||
| 7. Use setup.py to insatll the package. | |||
aaronmarkham
approved these changes
Oct 4, 2018
docs/install/windows_setup.md
Outdated
| 1. Download and install cuDNN. To get access to the download link, register as an NVIDIA community user. Then Follow the [link](http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows) to install the cuDNN. | ||
| 1. Unzip the file, rename it to ```OpenBLAS``` and put it under `C:\utils`. You can place the unzipped files and folders in another directory if you wish. | ||
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories and type `set OpenBLAS_HOME=C:\utils\OpenBLAS` on the command prompt(```cmd```). | ||
| 1. Download and install [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal). If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. Note that the lastest CUDA version supported by MXNet is 9.2. You can find it on the `Legacy Releases`. |
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lastest -> latest ?
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Where is Legacy Releases?
| @@ -141,10 +141,10 @@ To build and install MXNet yourself using [VS2017](https://www.visualstudio.com/ | |||
| 1. Set the environment variable `OpenCV_DIR` to point to the OpenCV build directory that you just unzipped. Start ```cmd``` and type `set OpenCV_DIR=C:\utils\opencv\build`. | |||
| 1. If you don’t have the Intel Math Kernel Library (MKL) installed, you can install it and follow the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md) from here, or you can use OpenBLAS. These instructions will assume you're using OpenBLAS. | |||
| 1. Download the [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.19/OpenBLAS-v0.2.19-Win64-int32.zip/download) package. Later versions of OpenBLAS are available, but you would need to build from source. v0.2.19 is the most recent version that ships with binaries. Contributions of more recent binaries would be appreciated. | |||
| 1. Unzip the file. You can place the unzipped files and folders in another directory if you wish. | |||
| 1. Unzip the file, rename it to ```OpenBLAS``` and put it under `C:\utils`. You can place the unzipped files and folders in another directory if you wish. | |||
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories and type `set OpenBLAS_HOME=C:\utils\OpenBLAS` on the command prompt(```cmd```). | |||
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Usually environment variables are all caps. why is it OpenBLAS_HOME?
| 1. Set the environment variable `OpenBLAS_HOME` to point to the OpenBLAS directory that contains the `include` and `lib` directories (e.g., `OpenBLAS_HOME = C:\utils\OpenBLAS`). | ||
| 1. Download and install [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal). If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. | ||
| 1. Download and install cuDNN. To get access to the download link, register as an NVIDIA community user. Then Follow the [link](http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows) to install the cuDNN. | ||
| 1. Unzip the file, rename it to ```OpenBLAS``` and put it under `C:\utils`. You can place the unzipped files and folders in another directory if you wish. |
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Did we provide command before to create C:\utils?
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Add this on line 140
sandeep-krishnamurthy
approved these changes
Oct 5, 2018
SamanthaFeidFischer
added a commit
to SamanthaFeidFischer/incubator-mxnet
that referenced
this pull request
Nov 17, 2018
* Change dependencies documentation opencv2-->opencv (#12654)
* opencv2-->opencv; deleted duplicate content
* update troubleshooting info
* fix bug, issue 12613 (#12614)
* [MXNET-780] Fix exception handling bug (#12051)
* Fix exception handling bug
* Trigger CI
* Add test for exc handling
* Trigger CI
* Resolve conflicts
* fix bug in prelu , issue 12061 (#12660)
* fix bug in prelu
* add unit test
* add mentions of the gluon toolkits and links to resources (#12667)
* add mentions of the gluon toolkits and links to resources
* fix nlp and cv text
* Remove fixed seed for test_ctc_loss (#12686)
* remove apachecon promo (#12695)
* Onnx version update from 1.2.1 to 1.3 in CI (#12633)
* upgrade onnx
* import helpers
* upgrade version in ci
* addressing comments
* fix
* test name changed
* retrigger tests
* adding comments
* [MXNET-833] [R] Char-level RNN tutorial fix (#12670)
* char RNN tutorial
* nit fixes
* Add documents for two new environment variables for memory pool. (#12668)
* document env.
* update.
* update.
* retrigger
* update mshadow for omp acceleration when nvcc is not present (#12674)
* update mshadow
* bump
* fix for test order (#12358)
* [MXNET-951] Python dockerfiles built on pip binaries and build/release script (#12556)
* Initial Commit for docker automation python
* Fixes
* change dir for tests
* Fix more issues
* fix docker tag command
* cosmetic changes
* update README
* update test to fail on version mismatch
* remove debug mode
* Update README.md
* Update README.md
* update README
* Add Licenses
* Some review comments
* Add Cuda80 and cuda92 dockerfiles and build steps
* Add renamed and hence untracked files for cu90
* Update README
* More ways to login
* Update README with login options
* Update README with links to test. test_mxnet link will work only after merge
* [MXNET-500]Test cases improvement for MKLDNN on Gluon (#10921)
* Rebase to align the latest changes on test_gluon.py
* Referring the issue link to skip message
* Retrigger the PRECI
* Remove previous changes
* Modify the cases trying to eliminate the errors on GPU
* Resolving conflict
* Further reduce the tensor size
* minor changes
* move to mkl
* fix flaky case
* Remove the test_mkldnn_gluon.py
* Move the cases back to test_gluon.py
* Enable test_gluon.test_export (#12688)
* Update contribute.md (#12685)
* Update contribute.md
Fixed grammar
* Update contribute.md
Fixed Grammar
* Update proposal_target.py (#12709)
* [MXNET-637] Multidimensional LSTM example for MXNetR (#12664)
* added R LSTM examples
* added tutorial to whitelist
* fix encoding
* added seed and fixed few formatting issues
* addressed PR comments
* formatting fixes'
* nit fixes
* fix epochs
* fixed tutorial link
* import Julia binding
- enable Jenkins CI build for Julia
- add license headers to Julia source code
- update links for Julia README
* Fix static / dynamic linking of gperftools and jemalloc (#12714)
* Disable test batchnorm slice (#12716)
* [MXNET-860] Use emplace where helpful (#12694)
* [MXNET-860] Use emplace where helpful
* [MXNET-860] Add emplace as an error in clang-tidy
* [MXNET-953] Correct ASAN cflags flag (#12659)
* [MXNET-860] Remove std::moves that have no affect (#12730)
* [MXNET-860] Remove std::moves that have no affect
* [MXNET-860] Check for unneeded moves as errors
* add FListInputNames attribute to softmax_cross_entropy (#12701)
* Fix #12672, importing numpy scalars (zero-dimensional arrays) (#12678)
* Fix https://github.com/apache/incubator-mxnet/issues/12672
Problem is in using np.ascontiguousarray,
which is buggy for zero-dimensional arrays
(see https://github.com/numpy/numpy/issues/5300 for details).
Here I use the solution proposed by numpy team:
switch to asarray with order='C'.
Add some tests for this situation (for array() and for setitem too).
* typo in tests
* [MXNET-908] Speed up travis builds to avoid timeouts (#12706)
This PR removes some redundant build tasks and removes some slow tests
to try and decrease the number of TravisCI timeouts that would otherwise
occur on large PRs.
* Throw exception if MXSymbolInferShape fails. (#12733)
* Throw exception if MXSymbolInferShape fails.
* scala-package/native/src/main/native/org_apache_mxnet_native_c_api.cc:
(Java_org_apache_mxnet_LibInfo_mxSymbolInferShape): throw
IllegalArgumentException with the content of MXGetError if call to
MXSymbolInferShape fails.
* Remove stray space.
* Don't throw in JNI.
checkCall in scala code will do the right thing with a nonzero exit
status.
* Don't repeat the memory free code.
Just wrap the FillSymbolInferShape calls in `if (ret == 0) { ... }`.
* Fix too-long line.
* [MXNET-716] Adding Scala Inference Benchmarks (#12721)
* Adding Scala Inference Benchmark base class + an example of how to run it
* Fixed scalastyle issues
* Added platform check to the classpath
* Formatting the metrics to print upto 2 decimal digits in float
* Added bash script to fetch resnet-18 data and params
* Added flag for cpu/gpu for running the script
* Fixed duplicate if check
* [MXNET-623] Fixing an integer overflow bug in large NDArray (#11742)
* Fix integer overflow when the array size is too large
* Update issue templates
* Update issue templates
* Remove files added by mistake
* Fix compilation error after type index_t changed to int64_t
* Explicity specify type in std::max template to avoid platform dependent compilation error
* Add nightly test for large array
* Update submodule mshadow
* Fix compilation warning
* Fix compilation warning
* Change index variable type to size_t
* Fix integer overflow when the array size is too large
* Update issue templates
* Remove files added by mistake
* Fix compilation error after type index_t changed to int64_t
* Explicity specify type in std::max template to avoid platform dependent compilation error
* Add nightly test for large array
* [MXNET-531] NeuralStyle Example for Scala (#11621)
* add initial neuralstyle and test coverage
* Add two more test and README
* kill comments
* patch on memory leaks fix
* fix formatting issues
* remove redundant files
* disable the Gan example for now
* add ignore method
* add new download scheme to match the changes
* Update submodule mshadow
* Fix compilation warning
* Fix compilation warning
* Change index variable type to size_t
* Change temp_size type from size_t to index_t
* Fix lint error
* Fix compilation error in GPU
* Fix compilation error on GPU
* Fix compilation error in cpp-package
* Fix unit test in GPU
* Change correct type for nnvmGraph
* update mshadow submodule to local repo to verify
* update mshadow submodule
* change some data type to size_t
* change unit test style
* fix lint
* fix compilation error in Windows
* fix compilation error in Windows
* use forked submodule to verify
* temporarily update submodule to verify the fix
* update mshadow submodule to use remote
* add test to nightly test script
* Change numpy version to 1.15.2 in python and docker install requirements (#12711)
Default numpy version in The Python Package Index (PyPI) is 1.15.2
* Reenable test_gluon.test_conv (#12718)
* reenable the test
* Trigger CI
* Refine mxnet python installation (#12696)
* update the installation document
* fix minor text
* update the rename process
* fix wording
* remind users. of env and vs version
* leave only the required dll
* fix the link
* update the R anchor
* refine the description of step 7
* add missing .
* fix spelling
* update links and fix wording
* Update packages and tests in the straight dope nightly (#12744)
* [#12345] Enabling two tests in the Straight Dope Nightly.
Two straight dope notebook tests were disabled due to a timeout so they
were disabled. I've updated one of the notebooks (rnn-gluon) to use the
gpu instead of the cpu so it takes ~ 5 minutes on a p3.2xl, and verified
the other notebook takes a minute and was a false alarm (visual-qa). The
PR in the Straight Dope is:
https://github.com/zackchase/mxnet-the-straight-dope/pull/540
* Add dependency for IPython update.
* Detect errors in notebook execution failure.
* Clean up of naming in retry code.
* Fix failing GPU test on single GPU host (kvstore) (#12726)
Fixes #10977
* Add option for automatic downcasting dtype for cudnn to allow using Tensorcore for fp32 (#12722)
* [MXNET-1026] [Perl] Sync with recent changes in Python's API (#12739)
* * Added randn function
* Internal SELU function on C++ layer
* Predict now accepts ndarray as well
* Gluon: Only warn when the blocks are unregistered.
* Better sparse support for gluon
* Gpu memory info via mxnet api call.
* Gluon: Improved block summary.
* Added validation docs for MXNet installation for Perl.
* Flexible perl env for examples.
* Gluon: Custom dtypes for the symbol block
* Separate eval metric for the epoch level.
* fixed typo.
* fix benchmark on control flow operators. (#12693)
* [MXNET-982] Provide example to illustrate usage of CSVIter in C++ API (#12636)
* Adding the example to demonstrate the usage of CSVIter
* Addressed the review comments to make the example configurable. Moved the unittests folder in 'examples' directory.
* Updated the code to address the cpp lint errors.
* Removed the author tag.
* Fixing the lint errors and usage message.
* Update README file for cpp-package and provide README file for example directory.
* Revert "Update README file for cpp-package and provide README file for example directory."
This reverts commit 02e784aaf927d465447d08a978b202bd5677a979.
These files were part of fix for JIRA issue 1017. These files were mistakenly committed in this PR.
* Addressed the review comments regarding usage of atoi and avoiding string copy.
* Updated to use strtol instead of atoi
* [MXNET-912] Refactoring ctc loss operator (#12637)
* Implement ctc_loss as a normal operator
* Update unit test
* Update unit test and fix bug in backward
* fix lint error
* refactoring
* Fix compilation error in CUDA
* Fix CPU compilation error
* Move ctc_include to nn folder and refactor
* temporarily disable lint on 3rd party includes
* move ctc_include to 3rdparty
* remove contrib ctc_loss operator
* revert a change by mistake
* Fix a bug in kDevCPU
* revert change by mistake
* add alias to make it backward compatible
* add unit test for backward compatibility
* linting
* Add new name to CONTRIBUTORS.md (#12763)
* Add resnet50-v1 to benchmark_score (#12595)
* add resnet50-v1 to benchmark_score
* rename back and duplicated
* rename v2 back to resnet.py
* [MXNET-716][MIRROR #12723] Scala Benchmark Extension pack (#12758)
* reflect the PR
* add 1 more metric
* Implement mkldnn convolution fusion and quantization. (#12530)
* Implement mkldnn convolution fusion.
Implement mkldnn convolution quantization.
* Fix lint
* Fix performance regression caused by mkldnn fallback.
* clean up include
* Fix msbuild on openmp pragma.
* Fix quantization test, allow to use original op names as exclude layer for quantization.
* Fix unittest.
* Fix unittest
* fix lint
* Add post quantize fusion
* add test case
* add head license in test case
* Remove GetBoolHash()
* Remove mkldnn fallback change.
* Address Haibin's comments.
* Add TIsMKLDNN for _sg_mkldnn_conv temporarily.
* Address reminisce's comments.
* Handle the case that inplace fail.
* pass unit test.
* Add symbol api get_backend_symbol()
* Retrigger ci
* update the test case
* Check subgraph index.
* Use index as FAvoidQuantizeInput's parameter.
* Add mkldnn_hwigo support as quantizaiton needs.
* Address KellenSunderland's comments.
* Handle input order change after subgraph pass.
* Fix ci test
* Introduction to Clojure-MXNet video link. (#12754)
* [MXNET-915] Java Inference API core wrappers and tests (#12757)
* Core Java API class commit
* Update ScalaStyle max line length to 132 instead of 100
* Disabled flaky test: test_mkldnn.test_Deconvolution (#12770)
* Add mkl-dnn to docker install method (#12643)
* add mkl-dnn to docker install method
* add mkl for gpu
* add docker for windows
* Improve mkldnn fallback. (#12663)
* Fix regression in MKLDNN caused by PR 12019 (#12740)
* add flag to elementwise_add
* fix flatteng
* retrigger
* Fixed broken link for Baidu's WARP CTC (#12774)
* Updated CONTRIBUTORS.md to include lebeg and gigasquid, moved mabreu to committers section (#12766)
* Use modern onnx API to load model from file (#12777)
* Update env_var.md (#12702)
* fix cnn visualization tutorial (#12719)
* [MXNET-979] Add fix_beta support in BatchNorm (#12625)
* Add fix_beta support in BatchNorm CPU implementation
* Fix lint checks. Update GPU tests
* Fix gpu tests
* make fix_beta not available for sparse. Update fix_beta for mkldnn
* Make default fix_beta to False for backward compatibility
* Add fix_beta to cudnn batchnorm operator
* Add tests for missing fix_beta and fix_gamma params
* fix indentation
* Fix failing tests
* simplify the cases with defaults for gamma, beta
* [MXNET-947] Expand scala imclassification example with resnet (#12639)
* [MXNET-947] Scala imclassification example with Resnet
* R fix metric shape (#12776)
* Revert "[MXNET-979] Add fix_beta support in BatchNorm (#12625)" (#12789)
This reverts commit 0bab6d529343f0ce186859ba75c9bb02067e9cfe.
Because master branch started to fail with this change.
* Updated tvm submodule head (#12764)
* Updated tvm submodule head
* Remove FInplaceIdentity attr for cast and _backward_cast
* Adagrad optimizer with row-wise learning rate (#12365)
* Proximal Group Adagrad optimizer
* Remove proximal implementation and rename to GroupAdagrad
* Remove superfluous doc
* Remove superfluous argument
* Fix mismatch shapes (#12793)
* mismatch shape switch
* closing bracket
* closing bracket
* Make Gluon download function to be atomic (#12572)
* use rename trick to achieve atomic write but didn't support python2 and windows
* add test for multiprocess download
* implement atomic_replace referred by https://github.com/untitaker/python-atomicwrites
* change the number of testing process to 10
* add docstring and disable linter
* half way to address some issue reviewer have
* use warning instead of raise UserWarn
* check for sha1
* Trigger CI
* fix the logic of checking hash
* refine the error message
* add more comments and expose the error message to the user
* delete trailing whitespace
* rename _path_to_encode to _str_to_unicode
* fix the error message bug and add remove when the movefile fail on windows
* add remove temp file for non-windows os
* handle the OSError caused by os.remove
* Trigger CI
* use finally to raise failure of atomic replace
* add missing try except block for os.remove
* add retries value to error message
* Re-enables test_dropout (#12717)
* [MXNET -1004] Poisson NegativeLog Likelihood loss (#12697)
* PoissonNLLLoss function to compute negative log likelihood loss
* Removing debugging print statements
* Pylint code formatting problems addressed
* Added Stirling approximation for factorial term in the denominator and test case for the same
* Separated the test cases for Flag value for logits and compute_full
* Added comments for package- numpy inclusion and some pylint formatting
* Trigger CI
* Markdown file updted. Added entry for Poissons NLLLoss
* Fixing pending documentation issue
* Documentation docstring changed
* PR Comment to remove extra newline removed.
* Symbol PI corrected
* epsilon spellicng correction
* More unit tests added - testing with mod.score() and mod.fit()
* changed the number of epochs
* PR Comments addressed added mod score tests and a newline
* Empty line added
* Adding hybridized test
* Trigger CI
* Variable names changed
* Update osx.mk - Added "apple" to USE_BLAS comment (#12819)
Added "apple" to USE_BLAS comment because it is one of the versions that are possible.
Currently the comment only has "mkl, blas, atlas, openblas" that can be used
* [MXNet-1002] Add GluonCV and NLP tookits, Keras, and developer wiki to navigation (#12704)
* refactor and sync nav bar between desktop and mobile
* update dev wiki url
* bump file for CI
* remove htaccess change from this pr
* removing keras for now
* bumping for CI
* fixed symbols naming in RNNCell, LSTMCell, GRUCell (#12794)
* fixed symbols naming in RNNCell and LSTMCell
* fixed GRUCell as well
* added test
* fixed tests?
* simplify mac mkldnn build (#12724)
* remove guard that prevent omp flag in mac
* udpate doc for mac make build
* update docs
* update readme
* set opencv to 1 in instructions
* remove disable opencv line
* update mac docs
* fix indent
* Change the way NDArrayIter handle the last batch (#12545)
* 1. move the shuffle to the reset 2. modify the roll_over behavior accordingly
* refactor the concat part
* refactor the code
* implement unit test for last_batch_handle
* refactor the getdata part
* add docstring and refine the code according to linter
* 1. add test case for NDArrayIter_h5py 2. refactor the implementation
* update contributions doc
* fix wording
* update doc for roll_over
* 1. add test for second iteration of roll_over 2. add shuffle test case
* fix some wording and refine the variables naming
* move utility function to new file
* move utility function to io_utils.py
* change shuffle function name to avoid redefining name
* make io as a module
* rename the utility functions
* disable wildcard-import
* fix the algorithm
* refactor the code
* test the NDArrayIter with different combinations of shuffle=True, data_source type and lables
* add edge case of label data for csr NDArrayIter
* trigger Travis CI
* handle the 'list' of data source
* check the list of data source
* fix the extra blank
* Trigger CI
* add _ to the utility functions
* Trigger CI
* update several test cases
* add test case for airbnb
* fix the typo
* fix wrong labels data shape
* switch the order of condition to make more sense
* [MXNET-707] Add unit test for mxnet to coreml converter (#11952)
* Add unittest to coreml converter
* Add unittest to coreml converter
* Add docstring and remove unused method
* updated test and removed unittest folder
* remove unittest
* Add coreml test to CI
* fix lint
* install mxnet-to-coreml for testing
* exclude test that takes too long
* linting to 100 max line width
* Add embedding to print_summary (#12796)
* Scala Docs - Replace old Symbol api usages (#12759)
* [MXNET-892] ONNX export/import: DepthToSpace, SpaceToDepth operators (#12731)
* ONNX export/import: DepthToSpace operator
* ONNX import/export: SpaceToDepth operator
* ONNX import/export: Tests for SpaceToDepth
* R install instructions update for macOS (#12832)
* add prereqs for R installation on Mac
* pin openblas for mac R install to 0.3.1
* Fixed __setattr__ method of _MXClassPropertyMetaClass (#12811)
* fixed indentation
* simplified code
* Fixed regex for matching platform type in Scala Benchmark scripts (#12826)
* Added context object to run TestCharRnn example (#12841)
* [MXNET-703] Show perf info for TensorRT during tests (#12656)
This PR makes sure perf information printed during TensorRT test runs
is correctly displayed when run in CI.
* Update Operator Implementation Tutorial (#12230)
* update op creation docs
* add flakiness checker and link to gradient checking
* address comments
* update reference line number
* fix comments
* Fix broken links (#12856)
* Fix Flaky Topk (#12798)
* fix flaky topk
* try to fix
* remove the usage of IndexFill
* fix
* add docstring
* Add Psroipooling CPU implementation (#12738)
* add psroipooling cpu impl
* minor fix
* revert copyright
* fix testcase
* add openmp
* no openmp for backward
* ONNX export: Fully connected operator w/o bias, ReduceSum, Square (#12646)
* ONNX export: Fully connected operator with no bias
* ONNX export: Helper function to convert bool string attributes to int
* ONNX export: ReduceSum operator
* ONNX import/export: Make pow backward compatible
* ONNX export: Square operator
* Undefined name: load_model() --> utils.load_model() (#12867)
* Undefined name: load_model() --> utils.load_model()
As discussed at:
* https://github.com/apache/incubator-mxnet/commit/815f36ce8b4ed16fe27d500f5c8c930cd10cee5c#r30956015
* Force a rebuild
* Force a rebuild
* ONNX export/import: Selu (#12785)
* Sparse support for logic ops (#12860)
* remove check
* fix lint
* fix gpu build
* add a tutorial for the subgraph API. (#12698)
* add tutorial.
* update.
* update.
* update.
* add test.
* fix subgraph test.
* update.
* update.
* update.
* add comments.
* remove test.
* update image path.
* update.
* update.
* update.
* fix lint.
* add link.
* fix lint.
* MKL-DNN Quantization Examples and README (#12808)
* add gluoncv support
* add ssd readme
* improve ssd readme
* add custom readme
* add ssd model link
* add squeezenet
* add ssd quantization script
* fix topo of args
* improve custom readme
* fix topo bug
* fix squeezenet
* add squeezenet accuracy
* Add initializer for min max to support quantization
* add dummy data inference
* add test case for init_param
* add subgraph docs
* improve docs
* add two models and fix default rgb_std to 1
* fix doc link
* improve MKLDNN_README
* add quantization for mobilenetv1
* fix ssd benchmark_score label shapes
* add resnet101_v1 and inceptionv3 support
* Refine some descriptions in the MKLDNN_README
* improve docs
* improve link in perf.md
* [MXNET-1033] Fix a bug in MultiboxTarget GPU implementation (#12840)
* remove num_labels check in multibox_target
* add unit test
* test both cpu and gpu
* add contrib operator to GPU unit test
* do not test all contrib operator in gpu
* [MXNET-1107] Fix CPUPinned unexpected behaviour (#12031)
* Fix CPUPinned unexpected behaviour
* fix lint
* add guards
* Actually, this may affect perf
* trigger ci
* fix lint
* fix documentation
* fix for dist_sync_device
* add guard
* fix bug with memory
* try fix for gluon mp interaction
* blah
* trigger jenkins
* Try fix for gluon multiprocessing bug
Thanks Nvidia!
* edit
* try nvidia fix
* address Haibin and Lin's comments
* get rid of blank line in Makefile
* NativeResource Management in Scala (#12647)
* add Generic MXNetHandle trait and MXNetHandlePhantomRef class that will be used by all MXNetObjects
* Generic Handle with AutoCloseable
* add NativeResource and NativeResourceManager with Periodic GC calling
* use NativeResource trait in NDArray, Symbol and Executor
* add run train mnist script
* create a Generic ResourceScope that can collect all NativeResources to dispose at the end
* modify NativeResource and ResourceScope, extend NativeResource in NDArray, Symbol and Executor
* remove GCExecutor
* deRegister PhantomReferences by when calling dispose()
* add Finalizer(temporary) to NativeResource
* refactor NativeResource.dispose() method
* update NativeResource/add Unit Test for NativeResource
* updates to NativeResource/NativeResourceRef and unit tests to NativeResource
* remove redundant code added because of the object equality that was needed
* add ResourceScope
* Fix NativeResource to not remove from Scope, add Unit Tests to ResourceScope
* cleanup log/print debug statements
* use TreeSet inplace of ArrayBuffer to speedup removal of resources from ResourceScope
Fix Executor dispose and make KVStore a NativeResource
* fix segfault that was happening because of NDArray creation on the fly in Optimizer
* Add comments for dispose(param:Boolean)
* add/update infer_range docs (#12879)
* Fix __all__ in optimizer/optimizer.py (#12886)
* Add index_copy() operator (#12810)
* add index_copy operator
* add index_copy op
* update index_copy op
* add unittest for index_copy()
* update index_copy
* update index_copy
* use mxnet_op::copy
* update index_copy
* update index_copy
* update index_copy
* update index_copy test
* update index_copy test
* sparse support for take(csr, axis=0) (#12889)
* initial commit
* add test cases for mode
* fix bug
* add comment
* more comments
* Add more models to benchmark_score (#12780)
* add models to cnn benchmark
* improve benchmark score
* add benchmark_gluon
* improve lint
* improve lint
* add licsence for script
* improve script lint
* mv benchmark_gluon to new location
* support multi-gpus
* Add a new parameter 'global batchsize' for the batch size multiplication for multi-gpu case
* add batch size argument help
* improve help and change default batchsize
* simplify benchmark_gluon
* [MXNET-1025] Add Jetpack 3.3 support to Jetson (#12735)
* Fix Batch input issue with Scala Benchmark (#12848)
* add initial change
* add fix
* improved usage of Shape as well as warning message on performance
* change into parallel
* drop dropBack
* apply Andrew's comments
* remove add dim inside img 2 pixel
* addressed Naveen's comment
* update comments
* fix type inference in index_copy. (#12890)
* Extending the DCGAN example implemented by gluon API to provide a more straight-forward evaluation on the generated image (#12790)
* add inception_score to metric dcgan model
* Update README.md
* add two pic
* updata readme
* updata
* Update README.md
* add license
* refine1
* refine2
* refine3
* fix review comments
* Update README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* Update example/gluon/DCGAN/README.md
* modify sn_gan file links to DCGAN
* update pic links to web-data
* update the pic path of readme.md
* rm folder pic/, and related links update to https://github.com/dmlc/web-data/mxnet/example/gluon/DCGAN/
* Update README.md
* [MXNET-674] Speed up GPU builds in CI (#12782)
* [MXNET-674] Speed up GPU builds in CI
* [MXNET-674] Refactor SMs into shell variable
* [MXNET-674] Build CMake GPU CI jobs without PTX
* [MXNET-793] ★ Virtualized testing in CI with QEMU ★ (#12094)
* virtual testing with qemu
* Add install procedure
* update installation
* Refine test run
* use direct ssh
* update readme
* Fix uneccesary cp
* Minor refinements
* Refine error conditions in startup
* requirements installed inside QEMU
* Update base image
* Fix license
* Dockerfile rename fallout
* license fixes
* refine documentation
* license fix
* update readme
* Update qemu base image and refine documentation
* Address CR comments wrt shebangs.
* Address CR comments wrt comments.
* adjust vda2 -> vda1
* Disable SMP, bug with newer kernel
* Remove commented out code
* Fix licenses
* CR comments addressed
* increase ram to 4096mb
* Revert dockerfile renaming
* Fix undo rename of dockerfiles
* Address CR comments
* CR
* [MXNET-1017] Updating the readme file for cpp-package and adding readme file for example directory. (#12773)
* Updating the readme file for cpp-package and adding readme file for example directory.
* Updating the readme file for cpp-package and adding readme file for example directory.
* Addressed the review comments.
* Addressed the review comments
* Fail the broken link job when broken links are found (#12905)
* Fix typo in formula in docstring for GRU cell and layer and add clarification to description (gluon.rnn) (#12896)
* Fix typo in GRU cell and layers (gluon.rnn) docstring
* empty
* fix the paths issue for downloading script (#12913)
* Ignore generated scala files. (#12928)
* use ResourceScope in Model/Trainer/FeedForward.scala (#12882)
* use ResourceScope in Model/Trainer/FeedForward.scala
* add moveToOuterScope public method to move resources to a outerScope if it exists
* fix memory leak in FeedForward.scala by making it a native resource and disposing argparams, auxParams
in dispose() method
* Disabled flaky test: test_gluon_gpu.test_slice_batchnorm_reshape_batchnorm (#12768)
* Fix the operator API documentation (#12942)
* Fix the operator API documentation
* update message
* fix indpt[0] for take(csr) (#12927)
* getnnz operator for CSR matrix (#12908)
* nnz
* update err msg
* skip nnz test on gpu
* fix broken docs (#12871)
* Add bytearray support back to imdecode (#12855, #12868) (#12912)
1. Avoid raise exception when input is bytearray.
2. Avoid OpenCV crash for empty input.
3. Added unittests.
* Update tree lstm example (#12960)
* update tree lstm example
* update README.md
* Update README.md
* Update bilstm integer array sorting example (#12929)
* Update the bilstm example to Gluon
* Update formating
* Update example/vae/VAE_example.ipynb
Co-Authored-By: ThomasDelteil <[email protected]>
* Fix the bug of assigning large integer to NDArray (#12921)
* remove num_labels check in multibox_target
* add unit test
* test both cpu and gpu
* add contrib operator to GPU unit test
* do not test all contrib operator in gpu
* Fix the large int assign problem
* Refactor mkldnn test files (#12410)
* move mkldnn helper funcs to diff file
* create test file to test helper functions
* update comments in header
* move helpers into include dir
* fix lint
* update comment
* add stdlib headers
* remove unused headers
* add endif
* add missing header
* add inlines
* fix lint
* move copyfrom test to mkldnn_test
* CudnnFind() usage improvements (#12804)
* Add mx.context.gpu_memory_info() to python api for flexible tests.
* Add test_gluon_gpu.py:test_large_models to show cudnnFind headroom issue.
* Output model sizes tried by test_gluon_gpu.py:test_large_models.
* Fix perl interface to MXGetGPUMemoryInformation.
* Increase difficulty of test_gluon_gpu.py:test_large_models.
* Forgot a file in fix for perl.
* Modify test to pass on no-cudnn CI runner.
* Mutex algo reg updates, serialize cudnnFind calls.
* Fix for cudnnFind memory headroom issue.
* Fix cpplint.
* Respond to reviewers comments.
* Guard against improper MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE values.
* Fix potentially unassigned var.
* fix mac r install and windows python build from source docs (#12919)
* fix mac r install and windows python build from source docs
* reorder macos r install instructions
* enable batchnorm unit tests (#12986)
* enable bn unit tests
* travis timed out, trigger ci
* Update CONTRIBUTORS.md (#12996)
I have made two minor contributions with pull requests so far. I forgot to add my name here earlier.
* fix Sphinx errors for tutorials and install ToCs (#12945)
* missing line break fix for tutorials toc
* fix the install index toc errors
* [MXNET -1030] Cosine Embedding Loss (#12750)
* COsine Embedding Loss function added
* Added unit tests for Cosine Embedding Loss Function
* Added Latex code for formula for cosine embedding loss
* Fixing document rendering
* Fixing documentation issue
* PR Comments addressed for using F (NDArray or Symbol) to calculate norm, renaming parameters
* Markdown file updated. Added entry for CosineEmbeddingLoss
* Added a line after .. math:: to fix documentation
* Documentation check - pylint fix
* Formula update
* Making the formula simpler for correct rendering incrementally - Update 1
* Making the formula simpler for correct rendering incrementally - Update 2
* Making the formula simpler for correct rendering incrementally - Update 3
* Making the formula simpler for correct rendering incrementally - Update 4
* Making the formula simpler for correct rendering incrementally - Update 5
* Trigger CI
* making the utility function cosine similarity internal
* Added a test case for label = -1, for dissimilar vectors
* Refactored names of parameters to the loss functions and updated the formula in docstring
* PR comments addressed changes in documentation
* Added random input vectors and labelled tests
* Renaming variables
* Pylint issues fixed
* Resolving conflicts
* Pylint issues fixed
* Style issues fixed trailing whitespaces removed
* Review comment addressed, sample_weight added in the parameter
* Trigger CI
* Reordered Parameter description
* comments addressed - spelling errors
* nit comments addressed
* Trigger CI
* Trugger CI
* Trigger CI
* Trigger CI
* [MXNET-1173] Debug operators - isfinite, isinf and isnan (#12967)
* is_finite and is_inf implementation for front-end python api debug operator
* updated unit-tests
* updated test cases and incorporated is_nan function
* solved index out of bounds issue and added comments
* simplified abs function call and added isnan to contrib.py and all debug ops to doc
* changed dimensions, added regular number, assert_equal instead of almost, removed ctx and added data.abs
* [MXNET-1111] Remove CPUPinned in ImageRecordIter (#12666)
* squash commit
* get rid of argument
* undo a lot of unnecessary changes
* undo more changes
* fix typo
* fix lint
* address comments and fix rebase mistake
* fix typo made during rebase
* revert cpu_pinned
* revert changes, because works without needing to copy params to GPU. thanks @yuxihu for testing and @apeforest for raising this issue!
* revert changes to comm and nccl
* Added/changed file_name, brief description comments in some files (#13033)
* sample_like operators (#13034)
* [MXNET-1179] Enforce deterministic algorithms in convolution layers (#12992)
* add env variable to choose deterministic cudnn alg
* set default value to false
* fix build failure in Windows GPU
* revert the previous change
* only check determinism in CUDNN 7.x release
* Add cudnn version check
* fix lint error
* Add a deprecate message (#13042)
* Fix the operator API documentation
* update message
* deprecate old command
* Disable flaky test test_operator.test_dropout (#13057)
* Disable flaky test test_prelu (#13060)
* la_op_inline.h to la_op-inl.h for consistency (#13045)
* la_op_inline.h to la_op-inl.h for consistency
* operator/tensor left-over doc changes
* Improve clojure tutorial (#12974)
* Switch tutorial to dependency/ies that exist on Maven
* Improve Clojure Module tutorial
* Add namespace docstring
* Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/module.html
* Add newlines for readability and to keep line length <80
* Nix duplicated section in Clojure Symbol API docs
"Multiple Outputs" is a (deprecated) repeat of "Group Multiple
Symbols".
* Improve Clojure Symbol tutorial
* Add namespace docstring
* Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/symbol.html
* Add newlines for readability and to keep line length <80
* Fix missing end-code-block in Clojure NDArray API docs
* Improve Clojure NDArray tutorial
* Add namespace docstring
* Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/ndarray.html
* Add newlines for readability and to keep line length <80
* Improve Clojure KVStore tutorial
* Add namespace docstring
* Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/kvstore.html
* Add newlines for readability and to keep line length <80
* [MXNET-1017] Updating the readme file for cpp-package and adding readme file for example directory. (#12773)
* Updating the readme file for cpp-package and adding readme file for example directory.
* Updating the readme file for cpp-package and adding readme file for example directory.
* Addressed the review comments.
* Addressed the review comments
* Fail the broken link job when broken links are found (#12905)
* Fix typo in formula in docstring for GRU cell and layer and add clarification to description (gluon.rnn) (#12896)
* Fix typo in GRU cell and layers (gluon.rnn) docstring
* empty
* fix the paths issue for downloading script (#12913)
* removed unused header (#13066)
* Moves f16c autodetection to its own cmake module (#12331)
* Set correct update on kvstore flag in dist_device_sync mode (#12786)
* Set correct update on kvstore flag in dist_device_sync mode
* Add warning message for batch-size change in dist mode
* Empty commit
* Fix lint issues
* ONNX export: Cleanup (#12878)
* ONNX export: Cleanup input retrieval
- Create a common function to get inputs for conversion functions
- Do not register functions if onnx is not found
* ONNX export: Add helper for creating node
* Maven Surefire bug workaround (#13081)
* remove legacy installation of Roxygen2 5.0 and add R-specific clean target (#12993) (#12998)
* remove installation of legacy Roxygen2 vers. 5.0
* add R-specific clean target (#12993)
* fixup! remove installation of legacy Roxygen2 vers. 5.0
* fixup! remove installation of legacy Roxygen2 vers. 5.0
* Gluon LSTM Projection and Clipping Support (#13056)
* support projection in LSTM
* add tests
* update rnn to use cudnn ex
* extend cudnn test to handle different versions
* add lstm clip
* use CUDNN_VERSION
* merge USE_CUDNN_LSTM_CLIP and USE_CUDNN_LSTM_PROJ
* assign false value to clip nan explicitly to RNN and GRU
* update test
* fix readme (#13082)
* [MXNET-1180] Scala Image API (#12995)
* add image and image suite
* apply toImage function and tests
* bug fix
* apply the commented change
* add test to apply border
* fix scalastyle
* [MXNET-793] Virtual testing with Qemu, refinement and extract test results to root MXNet folder (#13065)
* Improve Qemu infrastructure
Add documentation about running it interactively
* Separate provision
* Improve provisioning
* Refine provisioning and interactive
* Cant provision when the volumes arent mounted
* Fix running tests
* raise log output to INFO
* adjust logging
* flush stdout and stderr
* Refine by copying test results back to the host
* Fix license
* remove config file and different way to run QEMU
* remove config file and different way to run QEMU, remove ansible
* Updated / Deleted some examples (#12968)
* Updated / Deleted some examples
* remove onnx test
* remove onnx test
* Fix variable name in tutorial code snippet (#13052)
Fixes incorrect variable name in tutorial code as raised in issue https://github.com/apache/incubator-mxnet/issues/13051
* customized take forward for CPU (#12997)
* Update module example (#12961)
* Update Module example
* trigger CI
* ONNX export: Scalar, Reshape - Set appropriate tensor type (#13067)
np.array sets default dtype to float64 which is
not supported by ONNX. Setting these to appropriate type.
* Fix example for mxnet.nd.contrib.cond and fix typo in src/engine (#12954)
* fix typo in src/engine
* fix example for mx.nd.contrib.cond
* Improve the Clojure Package README to Make it Easier to Get Started (#12881)
* Improve the README and make it easier to get started
* Implement feedback from @ChaiBapchya and @daveliepmann
* combined deps
* Add wget
Co-Authored-By: gigasquid <[email protected]>
* WIP: update readme
* WIP: readme option 3
* Add section links to Clojure README
Link each install option with the corresponding README section
containing instructions for that option.
An existing link to Maven search is removed because it interferes with
the section links and it is replicated in the Option 1 instructions
below.
Per my PR suggestion:
https://github.com/apache/incubator-mxnet/pull/12881/files/22bbe55d8d62be9ff3aebf693f73fa6049afc01d#r226822148
* fix typo
Co-Authored-By: gigasquid <[email protected]>
* fix formatting
Co-Authored-By: gigasquid <[email protected]>
* fix formatting
Co-Authored-By: gigasquid <[email protected]>
* fix link
Co-Authored-By: gigasquid <[email protected]>
* Some more updates for the Clojure README
* [MXNET-918] Introduce Random module / Refact code generation (#13038)
* refactor code gen
* remove xxxAPIMacroBase (overkill)
* CI errors / scala-style
* PR review comments
* Fix a typo in operator guide (#13115)
* Fix the operator API documentation
* update message
* deprecate old command
* fix typo in op guide
* [Issue #11912] throw mxnet exceptions when decoding invalid images. (#12999)
* Raise an excption when passing an empty buffer to imdecode.
* src/io/image_io.cc: Check the length of the input buffer.
* tests/python/unittest/test_image.py: Update the (already existing) test to expect a mx.base.MXNetError.
* Raise an exception when passing an invalid data buffer to imdecode.
* src/io/image_io.cc: Raise an exception when the image could not be decoded instead of just logging.
* tests/python/unittest/test_image.py: Add a new test test_imdecode_invalid_image.
* Raise an exception when passing an invalid data buffer to imdecode.
* src/io/image_io.cc: Raise an exception when the image could not be decoded instead of just logging.
* tests/python/unittest/test_image.py: Add a new test test_imdecode_invalid_image.
* Rollback a "empty buffer" check in the image python bindings that's now more generally handled
in the core code.
* python/mxnet/image/image.py: remove buffer length check.
* Update adversary attack generation example (#12918)
* Fix adversary example generation
* Update README.md
* Fix test_utils.list_gpus()
* fix unused variable
* Disable travis tests (#13137)
* Update Gluon example folder (#12951)
* Reorganized the Gluon folder in example
* trigger CI
* update reference
* fix out of place accumulation
* Document the newly added env variable (#13049)
* add env variable to choose deterministic cudnn alg
* set default value to false
* fix build failure in Windows GPU
* revert the previous change
* only check determinism in CUDNN 7.x release
* Add cudnn version check
* fix lint error
* document env variable MXNET_ENFORCE_DETERMINISM
* use cudnnGet instead of cudnnFind when determinism required
* Revert "use cudnnGet instead of cudnnFind when determinism required"
This reverts commit d1bdf0f38f50b8c499f22ae1d50770b819f27678.
* Updated CONTRIBUTORS.md to include mxnet-label-bot (#13048)
* Updated CONTRIBUTERS.md to include label-bot
* Created section for label bot and included wiki page
* Moved Label Bot section in CONTRIBUTORS.md file to a more convenient location
* Retriggering
* Fix docker cleanup race condition (#13092)
* Improved git reset for CI builds (#12784)
* Refactor L2_normalization (#13059)
* Refactor L2_normalization
* Fix windows build
* Fix windows build
* Move cpu optimization into l2_normalization.cc
* Retrigger CI
* Retrigger CI
* Fix variational autoencoder example (#12880)
* Add documentation on GPU performance on Quantization example (#13145)
* Add documentation on GPU performance
* Update README.md
* [MXNET-1194] Reenable nightly tutorials tests for Python2 and Python3 (#13099)
* Reenable nightly tests tutorials
* small fix to settings
* optimize a few more tutorials
* Update tests
* Update runtime_functions.sh
* Update fine_tuning_gluon.md
* Update JenkinsfileForBinaries
* Update JenkinsfileForBinaries
* remove coverage
* Update dec example (#12950)
* update dec example
* trigger CI
* update to remove dependency on sklearn data
* Update MKL-DNN dependency (#12953)
* update mkldnn and fix conv/deconv
* fix
* fix indent
* fix cmake
* fix cmake
* fix cpp test for mkldnn
* fix typo
* fix conficts after merge
* debug: remove 5d test
* debug: remove 4d test
* add comments
* debug: remove 2d test
* update mklml in ci
* fix mklml
* Revert "fix mklml"
This reverts commit 328a22a373c49aacb914badd0db431bfbc8234f3.
* Revert "update mklml in ci"
This reverts commit 9ff3687892f85f43b8eac72ba935ceda928ae7e8.
* Revert "debug: remove 2d test"
This reverts commit 32551b3662fc30d5c9758a86c7664b4f2e367128.
* Revert "debug: remove 4d test"
This reverts commit 5412d643c2b00ce54c05e7387aca6779dee120d5.
* Revert "debug: remove 5d test"
This reverts commit 1fe9f8806d29c765e05f91c584799a947af2eb1d.
* debug illegal core dump
* debug illegal core dump
* Revert "debug illegal core dump"
This reverts commit 39321d578ae589465c0d4edcae7f92b88fdf3feb.
* Revert "debug illegal core dump"
This reverts commit 153b068b6d3a18a33f399076d3420ac42f2bc387.
* change cmake
* pin mkldnn version to 0.17rc
* change format number
* remove include directories in cmake
* fix cpp test
* address cpplint complaint
* remove comment code
* update mkldnn head
* License header (#13178)
* Minor fix to license_header documentation
* Handle UnicodeError when checking license
* Updated capsnet example (#12934)
* Updated capsnet
* trigger CI
* Update README.md
* Updates to several examples (#13068)
* Minor updates to several examples
* fix typo
* update following review
* Fix Sphinx python docstring formatting error. (#13177)
* [Doc] Fix repo paths in Ubuntu build doc (#13101)
* [Doc] Fix repo paths in Ubuntu build doc
* [Doc] Use relative path in Ubuntu build doc
* Update scala intellij tutorial (#12827)
* Update scala intellij tutorial
Update mxnet version
log4j fixes
Instructions from source
* Remove version numbers and various improvements
* Improve cpp-package example project build files. (#13093)
1. Change output to build folder.
2. Remove files that not been deleted by make clean.
* Fix Sphinx document parsing error. (#13195)
Fixes #12935
* Fix #13090, Add image.imread to python API doc. (#13176)
* Fix Sphinx docstring formatting error. (#13004, #13005, #13006) (#13175)
* Fix #12944, Fix Sphinx python docstring formatting error. (#13174)
* Fix #13013, Fix Sphinx python docstring error. (#13173)
* update the README (#13186)
* Fixed Sparse astype doc string formatting error (#13171)
* Fix problem with some OSX not handling the cast on imDecode (#13207)
* Port of scala Image API to clojure (#13107)
* Port of scala Image API to clojure
* Minor style changes
* Add specs and other minor fixes
* Fix unit tests (:facepalm:)
* Fixed Documentation issues (#13215)
1. mxnet.metric.EvalMetric.get_config doc error
2. mxnet.module.SequentialModule.add doc error
* update the doc (#13205)
* Fix Sphinx doc errors (#13170)
* Fix Sphinx python docstring error: initializer.InitDesc (#12939) (#13148)
* Fix Sphinx python docstring error: text contrib module (#12949) (#13149)
* Sphinx failure fixes (#13213)
* [MXNET-793] Virtualized ARMv7 with Qemu CI integration (#13203)
* Testing just ndarray, since otherwise we require test refactoring which will be done later
* Add QEMU ARMv7 test stage to CI
* test_ndarray fails, so change for test_engine until UT are fixed in ARM
* Refactor kvstore test (#13140)
* Refactor kvstore test
* Fix pylint
* Fix problem with some OSX not handling the cast on imDecode (#13207)
* Fix num_gpus
* remove unused variable rotateM_ (#10803)
* Revert "Sphinx failure fixes" (#13230)
* Revert "Refactor kvstore test (#13140)"
This reverts commit d8d2d6ef3d688a465e47f7170c2a11da804c2835.
* Revert "[MXNET-793] Virtualized ARMv7 with Qemu CI integration (#13203)"
This reverts commit fd3dedc621919b6fee7d8ca7fa2a85749e190907.
* Revert "Sphinx failure fixes (#13213)"
This reverts commit 2e4d6c8c1064b74d4e1c1b3441c2ecf12b81c6e2.
* [MXNET-953] Fix oob memory read (#12631)
* update log4j version of Scala package (#13131)
* Disable Flaky test test_operator.test_clip (#12902)
* Update multi-task learning example (#12964)
* Update multi task learning example
* Updating README.md
* Update MKLML dependency (#13181)
* update mkml
* refine DownloadMKLML.cmake
* merge DownloadMKLML.cmake from #11148
* fix mkldnn release version
* fix windows compilation
* Add --no-cache option to build.py when building containers (#13182)
Add functionality to build.py to disable caching
* Tool to ease compilation and reproduction of test results (#13202)
* Add tool to simplify reproducing tests
* add local build
* Add cmake_options.yaml
* minor
* Fix license
* Fix licenses
* Rename file, address CR comments about gpu build function
* Address Marco's comments
* support for upper triangular matrices in linalg (#12904)
* Fix Sphinx python docstrings (#13160)
* Doc fixes
* addressing feedback
* base_module fix
* fixing cross-reference issues
* Implemented a regression unit test for #11793 (#12975)
When using C++-based iterators, it's important that only a single batch is referenced at a time. Because C++
iterators are exposed to the Python code through a C API, there is no concept of reference counting. Hence,
typically C++ iterators will deallocate a batch when next() is called on them. So, we need to make sure the Python
code only references a single batch at a time, otherwise the Python code will attempt to access freed memory,
resulting in either (a) garbage accuracy or (b) a segmentation fault.
The test passes with the latest mxnet build. I verified it failed on previous releases, such as mxnet==1.2.0.
* Add Java API docs generation (#13071)
* add Java API docs generation; split out from Scala API docs
* bumping file for ci
* make scala docs build compatible for 2.11.x and 2.12.x scala
fix typo
* fix exit bug
* Fix Sphinx error in ONNX file (#13251)
* [Example] Fixing Gradcam implementation (#13196)
* fixing gradcam
* changed loading parameters code
* fixing type conversions issue with previous versions of matplotlib
* Fix test failure due to hybridize call in test_gluon_rnn.test_layer_fill_shape (#13043)
* Restore hybridize call in test_gluon_rnn.test_layer_fill_shape
* reset bulk_size when cached op forward hit error to fix the test failure
* add try-catch block to reset bulk_size in more places to prevent potential bugs
* more cleanup upon exception in Imperative::Backward
* Addressed sphinx build issue (#13246)
* Add gauss err function operator (#13229)
* erf
register gpu
* add doc
* Add Turing and Volta support to arch_name (#13168)
* Bugfix in ci/docker_cache.py (#13249)
* Fix scaladoc build errors (#13189)
* Fix scaladoc errors from missing classpath
Remove duplicate scalastyle plugin
* Fix scaladoc warnings
Also enable and fix all feature and deprecation warnings
* Add missing documentations for getnnz (#13128)
* Addressed ONNX module documentation warnings and added notes for short-form representation (#13259)
* Manually track num_max_thread (#12380)
* use cached version of get thread max
* reserve core affects omp singleton
* omp_thread_max_ updated in one line
* remove enabled block
* add brackets
* re-add excluded reserved
* add missing var
* refactor macro
* adding unit test for MKLDNN FullyConnected operator (#12985)
* adding unit test for MKLDNN FullyConnected operator
* removing mkldnn filter
* removing mkldnn filter
* Doc fixes (#13256)
* fix train mnist for inception-bn and resnet (#13239)
* Fix a bug in index_copy (#13218)
* fix.
* add test.
* retrigger
* Addressed doc issues (#13165)
* Addressed doc issues
* Update optimizer.py
* Force APT cache update before executing install (#13285)
* [Example] Gradcam consolidation in tutorial (#13255)
* fixing gradcam
* changed loading parameters code
* fixing type conversions issue with previous versions of matplotlib
* gradcam consolidation
* creating directory structures in utils
* changing location
* empty commit
* [MXNET-1203] Tutorial infogan (#13144)
* Adding info_gan example
* adjust paths of filenames
* Update index.md
* Update index.md
* Update index.md
* Update info_gan.md
Added an image
* Update info_gan.md
Applied some fixes
* Update info_gan.md
Applied some fixes
* Update info_gan.md
Applied some fixes
* Update info_gan.md
* Updated index.md file
* Updated index.md file
* change links
* Fixed typo
* Delete Untitled.ipynb
* Adding Vishaals comments
* Adding Anirudh's comments
* Fixed some bugs
* Adding Anirudh's comments
* some minor fixes
* Remove obsolete memory cost example (#13235)
* stop gap fix to let website builds through; scaladoc fix pending (#13298)
* Fix Sphinx errors in box_nms (#13261)
* Fix Sphinx errors (#13252)
* Sphinx errors in Gluon (#13275)
* Fix Sphinx python docstring formatting error. (#13194)
* Fix Sphinx python docstring formatting error (#13021).
Fixes #13021
* Update src/operator/nn/batch_norm.cc
Co-Authored-By: frankfliu <[email protected]>
* Visualization doc fix. Added notes for shortform (#13291)
* Addressed "dumplicate object reference" issues (#13214)
* Update basic_layers.py (#13299)
* add url and license to clojure package project (#13304)
* [Example] Add docstring for test optimizer and test score (#13286)
* update the doc for test_optimizer
* add docstring for test_score
* [Example] Update cpp example README (#13280)
* update the README to solve the library cannot find problem
* fix the broken format
* remove redundancy and broken format
* add .
* [Example]update NER example readme on module prediction (#13184)
* update readme on module prediction
* fix typo
* update url
* improve grammar
* update link
* [MXNET-1198] MXNet Java API (#13162)
* [MXNET-984] Add Java NDArray and introduce Java Operator Builder class (#12816)
* clean history and add commit
* add lint header
* bypass the java unittest when make the package
* clean up redundant test
* clean spacing issue
* revert the change
* clean up
* cleanup the JMacros
* adding line escape
* revert some changes and fix scala style
* fixes regarding to Naveen's comment
* Java Inference api and SSD example (#12830)
* New Java inference API and SSD example
* Adding license to java files and fixing SSD example
* Fixing SSD example to point to ObjectDetector instead of ImageClassifier
* Make scripts for object detector independent to os and hw cpu/gpu
* Added API Docs to Java Inference API. Small fixes for PR
* Cosmetic updates for API DOCS requested during PR
* Attempt to fix the CI Javafx compiler issue
* Migrate from Javafx to apache commons for Pair implementation
* Removing javafx from pom file
* Fixes to appease the ScalaStyle deity
* Minor fix in SSD script and Readme
* Added ObjectDetectorOutput which is a POJO for Object Detector to simplify the return type
* Removing Apache Commons Immutable Pair
* Adding license to new file
* Minor style fixes
* minor style fix
* Updating to be in scala style and not explicitly declare some unnecessary variables
* NativeResource Management in Scala (#12647) (#12883)
* add Generic MXNetHandle trait and MXNetHandlePhantomRef class that will be used by all MXNetObjects
* Generic Handle with AutoCloseable
* add NativeResource and NativeResourceManager with Periodic GC calling
* use NativeResource trait in NDArray, Symbol and Executor
* add run train mnist script
* create a Generic ResourceScope that can collect all NativeResources to dispose at the end
* modify NativeResource and ResourceScope, extend NativeResource in NDArray, Symbol and Executor
* remove GCExecutor
* deRegister PhantomReferences by when calling dispose()
* add Finalizer(temporary) to NativeResource
* refactor NativeResource.dispose() method
* update NativeResource/add Unit Test for NativeResource
* updates to NativeResource/NativeResourceRef and unit tests to NativeResource
* remove redundant code added because of the object equality that was needed
* add ResourceScope
* Fix NativeResource to not remove from Scope, add Unit Tests to ResourceScope
* cleanup log/print debug statements
* use TreeSet inplace of ArrayBuffer to speedup removal of resources from ResourceScope
Fix Executor dispose and make KVStore a NativeResource
* fix segfault that was happening because of NDArray creation on the fly in Optimizer
* Add comments for dispose(param:Boolean)
* Added unit tests for Resource Scope in Java (#12955)
* Bumping down minimum java support from 8 to 7 (#12965)
* [MXNET-984] Java NDArray Documentation Generation (#12835)
* cherry pick javaDoc changes
* update NDArray changes
* refactoring change and merge all docGen in a single place
* clean the scalastyle
* take on Piyush nit
* drop the comments
* First pass at adding JavaDocs for new java api classes (#12963)
* First pass at adding JavaDocs for new java api classes
* Fix a scalastyle issue
* Updating JavaDoc based on feedback
* [MXNET-1160] add Java build/run example (#12969)
* add example
* clean up nit
* find the pain point
* add java tut into whitelist
* Trigger CI
* add java demo and split scala demo
* address the comments
* change the examples
* fix the wrong configuration
* Maven Surefire bug workaround (#13097)
* use ResourceScope in Model/Trainer/FeedForward.scala (#12882) (#13164)
* use ResourceScope in Model/Trainer/FeedForward.scala
* add moveToOuterScope public method to move resources to a outerScope if it exists
* fix memory leak in FeedForward.scala by making it a native resource and disposing argparams, auxParams
in dispose() method
* [MXNET-1187] Added Tutorial for Java under mxnet.io/docs/tutorials (#13183)
* Added tutorial for Java installation on IntelliJ for mxnet.io website
* Added correct image resources
* Removed spurious quotes
* Added java tutorial to whitelisting
* Added community download edition link to intelliJ section
* [MXNET-1202] Change Builder class into a better way (#13159)
* applying changes for Builder functions
* simplify the code structure
* update docgen
* follow Naveen's suggestion
* apply comments to Param
* clean up param build
* change on the comments
* add one description line
* [MXNET-1041] Add Java benchmark (#13095)
* add java benchmark
* applied changes based on Piyush comments
* applies Andrew's change
* fix clojure test issue
* update the statistic names
* follow Naveen's instruction
* [MXNET-918] [Introduce Random module / Refact code generation (#13038)][Cherry pick] (#13242)
* [MXNET-918] Introduce Random module / Refact code generation (#13038)
* refactor code gen
* remove xxxAPIMacroBase (overkill)
* CI errors / scala-style
* PR review comments
* clean up the duplicated code
* add comments
* Fixed missing break statement (#13257)
* Java Benchmark failure (#13258)
* patch fix
* update ignore
* rename getContext to bindToDevice
* Update JavaBenchmark.java
* Addressing PR feedback for merging Java API into master (#13277)
* Addressing PR feedback for merging Java API into master
* Changed constructors to package private instead of private
* clean up the NDArray follow the comments (#13281)
* [MXNET-1181] Added command line alternative to IntelliJ in install instructions (#13267)
* Added command line alternative to IntelliJ
* Removed the duplicate file
* Fixed typos
* Fixed minor command issue
* add defaults and clean up the tests (#13295)
* [MXNET-1187] Added Java SSD Inference Tutorial for website (#13201)
* Added Java SSD Inference Tutorial for website
* Added whitelisting to SSD tutorial
* Address PR feedback
* Marking intelliJ as optional
* [MXNET-1182] Predictor example (#13237)
* add initial commit
* push back predictor
* name fix and bug fix
* update readme and script to run
* minor fix
* minor fix
* fix on doc
* update predictor
* Reducing the length of setup tutorial (#13306)
* enabling test_dropout after fixing flaky issue (#13276)
* enabling test_dropout after fixing flaky issue
* adding a check for positive seed
* fix the flag (#13293)
* Made fixes to sparse.py and sparse.md (#13305)
* Fix descriptions in scaladocs for macro ndarray/sybmol APIs (#13210)
* [Example] Gradcam- Fixing a link (#13307)
* fixing gradcam
* changed loading parameters code
* fixing type conversions issue with previous versions of matplotlib
* gradcam consolidation
* creating directory structures in utils
* changing location
* empty commit
* fix file lock issue
* fix link
* removing other commits
* remove commit
* Updated the Instructions for use of the label bot (#13192)
* Updated Instructions for Label Bot
* Updated instructions for mxnet-label-bot
* Including myself as a contributor
* Clarified usage of label bot
* Fixed typos and instructions/examples have been made more clear
* Added link for available labels
* [MXNET-33] Enhance mkldnn pooling to support full convention (#11047)
* fix mkldnn pooling to support full convention
* backward with full convention
* fix
* add pooling test for full convention
* add function for computing padding size
* fix unit test
* only support max-pooling
* fix pooling bwd
* address review comment
* [MXNET-1213] add Cent OS build for Scala (#13279)
* add centos build for Scala
* migrate the build portion to docker
* update build script and chmod +x
* address Jenkins change
* allow CentOS provide all depdencies
* fix file lock issue (#13296)
* modify code for working in gpu context. (#13302)
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Description
Update the doc to install python language binding.
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Please feel free to remove inapplicable items for your PR.
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@aaronmarkham @ankkhedia