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Sentiment analysis failures: invalid device function #34

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elvinpoon opened this issue Sep 3, 2016 · 3 comments
Closed

Sentiment analysis failures: invalid device function #34

elvinpoon opened this issue Sep 3, 2016 · 3 comments

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@elvinpoon
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Here is the error code.

./train.sh
I0903 14:10:57.917793 18690 Util.cpp:144] commandline: /data2/package/pypaddle/bin/../opt/paddle/bin/paddle_trainer --config=trainer_config.py --save_dir=./model_output --job=train --use_gpu=1 --trainer_count=4 --num_passes=10 --log_period=10 --dot_period=20 --show_parameter_stats_period=100 --test_all_data_in_one_period=1
I0903 14:11:01.704715 18690 Util.cpp:113] Calling runInitFunctions
I0903 14:11:01.705032 18690 Util.cpp:126] Call runInitFunctions done.
[INFO 2016-09-03 14:11:02,367 networks.py:1122] The input order is [word, label]
[INFO 2016-09-03 14:11:02,368 networks.py:1129] The output order is [__cost_0__]
I0903 14:11:02.395427 18690 Trainer.cpp:169] trainer mode: Normal
I0903 14:11:02.395754 18690 MultiGradientMachine.cpp:108] numLogicalDevices=1 numThreads=4 numDevices=4
F0903 14:11:02.400593 18690 hl_gpu_matrix_kernel.cuh:181] Check failed: cudaSuccess == err (0 vs. 8) [hl_gpu_apply_unary_op failed] CUDA error: invalid device function
*** Check failure stack trace: ***
    @     0x7fc9c37175cd  google::LogMessage::Fail()
    @     0x7fc9c3719433  google::LogMessage::SendToLog()
    @     0x7fc9c371715b  google::LogMessage::Flush()
    @     0x7fc9c3719e1e  google::LogMessageFatal::~LogMessageFatal()
    @           0x7d65b2  hl_gpu_apply_unary_op<>()
    @           0x79d156  paddle::BaseMatrixT<>::applyUnary<>()
    @           0x79ccf0  paddle::BaseMatrixT<>::applyUnary<>()
    @           0x780733  paddle::BaseMatrixT<>::zero()
    @           0x561960  paddle::Parameter::enableType()
    @           0x564531  paddle::parameterInitNN()
    @           0x567fe9  paddle::NeuralNetwork::init()
    @           0x55ee4b  paddle::TrainerThread::TrainerThread()
    @           0x55fab7  paddle::MultiGradientMachine::MultiGradientMachine()
    @           0x58788e  paddle::GradientMachine::create()
    @           0x6e296d  paddle::TrainerInternal::init()
    @           0x6dc144  paddle::Trainer::init()
    @           0x54622d  main
    @     0x7fc9c2699830  __libc_start_main
    @           0x54db19  _start
    @              (nil)  (unknown)
/data2/package/pypaddle/bin/paddle: line 46: 18690 Aborted                 ${DEBUGGER} $MYDIR/../opt/paddle/bin/paddle_trainer ${@:2}
@gangliao
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gangliao commented Sep 3, 2016

#18 Looks like you use cuda 8.0 with modern Gpu.

invalid device function indicates that you have a CUDA / GPU incompatibility.
Maybe you can modify CMake to fix it.

open cmake/flags.cmake and add following code:

if (CUDA_VERSION VERSION_GREATER "8.0")

list(APPEND __arch_flags " -gencode arch=compute_60,code=sm_60")

endif()

then, rebuild the project

@elvinpoon
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I tried this but it doesn't work...same error

@gangliao
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gangliao commented Oct 8, 2016

Fix CUDA_VERSION Comparsion #165

qingqing01 pushed a commit to qingqing01/Paddle that referenced this issue Apr 30, 2020
zhangting2020 pushed a commit to zhangting2020/Paddle that referenced this issue Aug 25, 2021
KPatr1ck pushed a commit to KPatr1ck/Paddle that referenced this issue Sep 10, 2021
XiaoguangHu01 pushed a commit that referenced this issue Sep 18, 2021
* 1. add interface for fft;
2. add data type predicate;
3. fix paddle.roll.

* add fft c2c cufft kernel

* implement argument checking & op calling parts for fft_c2c and fftn_c2c

* add operator and opmaker definitions

* only register float and double for cpu.

* add common code for implementing FFT, add pocketfft as a dependency

* add fft c2c cufft kernel function

* fix bugs in python interface

* add support for c2r, r2c operators, op makers, kernels and kernel functors.

* test and fix bugs

* 1. fft_c2c function: add support for onesided=False;
2. add complex<float>, complex<double> support for concat and flip.

* 1. fft: fix python api bugs;
2. shape_op: add support for complex data types.

* fft c2c cufft kernel done with complie and link

* fix shape_op, add mkl placeholder

* remove mkl

* complete fft c2c in gpu

* 1. implement mkl-based fft, FFTC2CFunctor and common function exec_fft;
2. change the design, add input and output typename as template parameter for all FFTFunctors, update pocketfft-based implementation.

* complete fft c2c on gpu in ND

* complete fft c2c on gpu in ND

* complete fft c2c backward in ND

* fix MKL-based implementation

* Add frame op and CPU/GPU kernels.

* Add frame op forward unittest.

* Add frame op forward unittest.

* Remove axis parameter in FrameFunctor.

* Add frame op grad CPU/GPU kernels and unittest.

* Add frame op grad CPU/GPU kernels and unittest.

* Update doc string.

* Update after review and remove librosa requirement in unittest.

* Update grad kernel.

* add fft_c2r op

* Remove data allocation in TransCompute function.

* add fft r2c onesided with cpu(pocketfft/mkl) and gpu

* last fft c2r functor

* fix C2R and R2C for cufft, becase the direction is not an option in these cases.

* add fft r2c onesided with cpu(pocketfft/mkl) and gpu

* fix bugs in python APIs

* fix fft_c2r grad kernal

* fix bugs in python APIs

* add cuda fft c2r grad kernal functor

* clean code

* fix fft_c2r python API

* fill fft r2c result with conjugate symmetry (#19)

fill fft r2c result with conjugate symmetry

* add placeholder for unittests (#24)

* simple parameterize test function by auto generate test case from parm list (#25)

* miscellaneous fixes for python APIs (#26)

* add placeholder for unittests

* resize fft inputs before computation is n or s is provided.

* add complex kernels for pad and pad_grad

* simplify argument checking.

* add type promotion

* add int to float or complex promotion

* fix output data type for static mode

* fix fft's input dtype dispatch, import fft to paddle

* fix typos in axes checking (#27)

* fix typos in axes checking

* fix argument checking (#28)

* fix argument checking

* Add C2R Python layer normal and abnormal use cases (#29)

* documents and single case

* test c2r case

* New C2R Python layer normal and exception use cases

* complete rfft,rfft2,rfftn,ihfft,ihfft2,ihfftn unittest and doc string (#30)

* Documentation of the common interfaces of c2r and c2c (#31)

* Documentation of the common interfaces of c2r and c2c

* clean c++ code  (#32)

* clean code

* Add numpy-based implementation of spectral ops (#33)

* add numpy reference implementation of spectral ops

* Add fft_c2r numpy based implementation for unittest. (#34)

* add fft_c2r numpy implementation

* Add deframe op and stft/istft api. (#23)

* Add frame api

* Add deframe op and kernels.

* Add stft and istft apis.

* Add deframe api. Update stft and istft apis.

* Fix bug in frame_from_librosa function when input dims >= 3

* Rename deframe to overlap_add.

* Update istft.

* Update after code review.

* Add overlap_add op and stft/istft api unittest (#35)

* Add overlap_add op unittest.

* Register complex kernels of squeeze/unsquuze op.

* Add stft/istft api unittest.

* Add unittest for fft helper functions (#36)

* add unittests for fft helper functions. add complex kernel for roll op.

* complete static graph unittest for all public api (#37)

* Unittest of op with FFT C2C, C2R and r2c added (#38)

* documents and single case

* test c2r case

* New C2R Python layer normal and exception use cases

* Documentation of the common interfaces of c2r and c2c

* Unittest of op with FFT C2C, C2R and r2c added

Co-authored-by: lijiaqi <[email protected]>

* add fft related options to CMakeLists.txt

* fix typos and clean code (#39)

* fix invisible character in mkl branch and fix error in error message

* clean code: remove docstring from unittest for signal.py.

* always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype. (#40)

* always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype.

* fix CI Errors: numpy dtype comparison, thrust when cuda is not available (#41)

1. always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype.
2. promote floating point tensor to complex tensor ior fft_c2c and fft_c2r;
3. fix unittest to catch UnImplementedError and RuntimeError;
4. fix compile error by avoid using thrust when cuda is not available.
5.  fix sample code, use paddle.fft instead of paddle.tensor.fft

* remove inclusion of thrust, add __all__ list for fft (#42)

* Add api doc and update unittest. (#43)

* Add doc strings.
* Update overlap_add op unittest

* fix MKL-based FFT implementation (#44)

* fix MKL-based FFT implementation, MKL CDFT's FORWARD DOMAIN is always REAL for R2C and C2R

* remove code for debug (#45)

* use dynload for cufft (#46)

* use std::ptrdiff_t as datatype of stride (instead of int64_t) to avoid argument mismatch on some platforms.

* add complex support for fill_zeros_like

* use dynload for cufft

* Update doc and unittest. (#47)

* Add doc of frame op and overlap_add op.

* Update unittest.

* use dynload for cufft (#48)

1. use dynload for cufft
2. fix unittest;
3. temporarily disable Rocm.

* fix conflicts and merge upstream (#49)

fix conflicts and merge upstream

* fix compile error: only link dyload_cuda when cuda is available (#50)

* fix compile error: only link dyload_cuda when cuda is available

* fix dynload for cufft on windows (#51)

1. fix dynload for cufft on windows;
2. fix unittests.

* add NOMINMAX to compile on windows (#52)

 add NOMINMAX to compile on windows

* explicitly specify capture mode for lambdas (#55)

 explicitly specify capture mode for lambdas

* fix fft sample (#53)

* fix fft sample

* update scipy and numpy version for unittests of fft (#56)

update scipy and numpy version for unittests of fft

* Add static graph unittests of frame and overlap_add api. (#57)

* Remove cache of cuFFT & Disable ONEMKL (#59)

1. replace numpy.fft with scipy.fft as numpy<1.20 not support ortho norm
2. remove cache of cufft plans;
3. enhance error checking.
4. default WITH_ONEMKL to OFF

Co-authored-by: jeff41404 <[email protected]>
Co-authored-by: root <[email protected]>
Co-authored-by: KP <[email protected]>
Co-authored-by: lijiaqi <[email protected]>
Co-authored-by: Xiaoxu Chen <[email protected]>
Co-authored-by: lijiaqi0612 <[email protected]>
AnnaTrainingG pushed a commit to AnnaTrainingG/Paddle that referenced this issue Sep 29, 2021
* 1. add interface for fft;
2. add data type predicate;
3. fix paddle.roll.

* add fft c2c cufft kernel

* implement argument checking & op calling parts for fft_c2c and fftn_c2c

* add operator and opmaker definitions

* only register float and double for cpu.

* add common code for implementing FFT, add pocketfft as a dependency

* add fft c2c cufft kernel function

* fix bugs in python interface

* add support for c2r, r2c operators, op makers, kernels and kernel functors.

* test and fix bugs

* 1. fft_c2c function: add support for onesided=False;
2. add complex<float>, complex<double> support for concat and flip.

* 1. fft: fix python api bugs;
2. shape_op: add support for complex data types.

* fft c2c cufft kernel done with complie and link

* fix shape_op, add mkl placeholder

* remove mkl

* complete fft c2c in gpu

* 1. implement mkl-based fft, FFTC2CFunctor and common function exec_fft;
2. change the design, add input and output typename as template parameter for all FFTFunctors, update pocketfft-based implementation.

* complete fft c2c on gpu in ND

* complete fft c2c on gpu in ND

* complete fft c2c backward in ND

* fix MKL-based implementation

* Add frame op and CPU/GPU kernels.

* Add frame op forward unittest.

* Add frame op forward unittest.

* Remove axis parameter in FrameFunctor.

* Add frame op grad CPU/GPU kernels and unittest.

* Add frame op grad CPU/GPU kernels and unittest.

* Update doc string.

* Update after review and remove librosa requirement in unittest.

* Update grad kernel.

* add fft_c2r op

* Remove data allocation in TransCompute function.

* add fft r2c onesided with cpu(pocketfft/mkl) and gpu

* last fft c2r functor

* fix C2R and R2C for cufft, becase the direction is not an option in these cases.

* add fft r2c onesided with cpu(pocketfft/mkl) and gpu

* fix bugs in python APIs

* fix fft_c2r grad kernal

* fix bugs in python APIs

* add cuda fft c2r grad kernal functor

* clean code

* fix fft_c2r python API

* fill fft r2c result with conjugate symmetry (#19)

fill fft r2c result with conjugate symmetry

* add placeholder for unittests (#24)

* simple parameterize test function by auto generate test case from parm list (#25)

* miscellaneous fixes for python APIs (#26)

* add placeholder for unittests

* resize fft inputs before computation is n or s is provided.

* add complex kernels for pad and pad_grad

* simplify argument checking.

* add type promotion

* add int to float or complex promotion

* fix output data type for static mode

* fix fft's input dtype dispatch, import fft to paddle

* fix typos in axes checking (#27)

* fix typos in axes checking

* fix argument checking (#28)

* fix argument checking

* Add C2R Python layer normal and abnormal use cases (#29)

* documents and single case

* test c2r case

* New C2R Python layer normal and exception use cases

* complete rfft,rfft2,rfftn,ihfft,ihfft2,ihfftn unittest and doc string (PaddlePaddle#30)

* Documentation of the common interfaces of c2r and c2c (PaddlePaddle#31)

* Documentation of the common interfaces of c2r and c2c

* clean c++ code  (PaddlePaddle#32)

* clean code

* Add numpy-based implementation of spectral ops (PaddlePaddle#33)

* add numpy reference implementation of spectral ops

* Add fft_c2r numpy based implementation for unittest. (PaddlePaddle#34)

* add fft_c2r numpy implementation

* Add deframe op and stft/istft api. (#23)

* Add frame api

* Add deframe op and kernels.

* Add stft and istft apis.

* Add deframe api. Update stft and istft apis.

* Fix bug in frame_from_librosa function when input dims >= 3

* Rename deframe to overlap_add.

* Update istft.

* Update after code review.

* Add overlap_add op and stft/istft api unittest (PaddlePaddle#35)

* Add overlap_add op unittest.

* Register complex kernels of squeeze/unsquuze op.

* Add stft/istft api unittest.

* Add unittest for fft helper functions (PaddlePaddle#36)

* add unittests for fft helper functions. add complex kernel for roll op.

* complete static graph unittest for all public api (PaddlePaddle#37)

* Unittest of op with FFT C2C, C2R and r2c added (PaddlePaddle#38)

* documents and single case

* test c2r case

* New C2R Python layer normal and exception use cases

* Documentation of the common interfaces of c2r and c2c

* Unittest of op with FFT C2C, C2R and r2c added

Co-authored-by: lijiaqi <[email protected]>

* add fft related options to CMakeLists.txt

* fix typos and clean code (PaddlePaddle#39)

* fix invisible character in mkl branch and fix error in error message

* clean code: remove docstring from unittest for signal.py.

* always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype. (PaddlePaddle#40)

* always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype.

* fix CI Errors: numpy dtype comparison, thrust when cuda is not available (PaddlePaddle#41)

1. always convert numpy array to paddle.Tensor to avoid comparing numpy dtype with paddle dtype.
2. promote floating point tensor to complex tensor ior fft_c2c and fft_c2r;
3. fix unittest to catch UnImplementedError and RuntimeError;
4. fix compile error by avoid using thrust when cuda is not available.
5.  fix sample code, use paddle.fft instead of paddle.tensor.fft

* remove inclusion of thrust, add __all__ list for fft (PaddlePaddle#42)

* Add api doc and update unittest. (PaddlePaddle#43)

* Add doc strings.
* Update overlap_add op unittest

* fix MKL-based FFT implementation (PaddlePaddle#44)

* fix MKL-based FFT implementation, MKL CDFT's FORWARD DOMAIN is always REAL for R2C and C2R

* remove code for debug (PaddlePaddle#45)

* use dynload for cufft (PaddlePaddle#46)

* use std::ptrdiff_t as datatype of stride (instead of int64_t) to avoid argument mismatch on some platforms.

* add complex support for fill_zeros_like

* use dynload for cufft

* Update doc and unittest. (PaddlePaddle#47)

* Add doc of frame op and overlap_add op.

* Update unittest.

* use dynload for cufft (PaddlePaddle#48)

1. use dynload for cufft
2. fix unittest;
3. temporarily disable Rocm.

* fix conflicts and merge upstream (PaddlePaddle#49)

fix conflicts and merge upstream

* fix compile error: only link dyload_cuda when cuda is available (PaddlePaddle#50)

* fix compile error: only link dyload_cuda when cuda is available

* fix dynload for cufft on windows (PaddlePaddle#51)

1. fix dynload for cufft on windows;
2. fix unittests.

* add NOMINMAX to compile on windows (PaddlePaddle#52)

 add NOMINMAX to compile on windows

* explicitly specify capture mode for lambdas (PaddlePaddle#55)

 explicitly specify capture mode for lambdas

* fix fft sample (PaddlePaddle#53)

* fix fft sample

* update scipy and numpy version for unittests of fft (PaddlePaddle#56)

update scipy and numpy version for unittests of fft

* Add static graph unittests of frame and overlap_add api. (PaddlePaddle#57)

* Remove cache of cuFFT & Disable ONEMKL (PaddlePaddle#59)

1. replace numpy.fft with scipy.fft as numpy<1.20 not support ortho norm
2. remove cache of cufft plans;
3. enhance error checking.
4. default WITH_ONEMKL to OFF

Co-authored-by: jeff41404 <[email protected]>
Co-authored-by: root <[email protected]>
Co-authored-by: KP <[email protected]>
Co-authored-by: lijiaqi <[email protected]>
Co-authored-by: Xiaoxu Chen <[email protected]>
Co-authored-by: lijiaqi0612 <[email protected]>
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