Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU #13333

larroy · 2018-11-20T09:32:10Z

Description

C++ unit tests failing on CPU without MKL

ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU
ACTIVATION_PERF.TimingCPU

Environment info (Required)

----------Python Info----------
Version      : 3.5.2
Compiler     : GCC 5.4.0 20160609
Build        : ('default', 'Nov 23 2017 16:37:01')
Arch         : ('32bit', 'ELF')
------------Pip Info-----------
Version      : 18.1
Directory    : /home/piotr/devel/mxnet/mxnet_py3/lib/python3.5/site-packages/pip
----------MXNet Info-----------
Version      : 1.3.1
Directory    : /home/piotr/devel/mxnet/python/mxnet
Hashtag not found. Not installed from pre-built package.
----------System Info----------
Platform     : Linux-3.4.113-sun7i-armv7l-with-Ubuntu-16.04-xenial
system       : Linux
node         : bananapipro
release      : 3.4.113-sun7i
version      : #16 SMP PREEMPT Wed Jan 24 19:20:59 CET 2018
----------Hardware Info----------
machine      : armv7l
processor    : armv7l
Architecture:          armv7l
Byte Order:            Little Endian
CPU(s):                2
On-line CPU(s) list:   0,1
Thread(s) per core:    1
Core(s) per socket:    2
Socket(s):             1
CPU max MHz:           1008.0000
CPU min MHz:           60.0000
Hypervisor vendor:     (null)
Virtualization type:   full
----------Network Test----------
Setting timeout: 10
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.2887 sec, LOAD: 1.0031 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0704 sec, LOAD: 1.3277 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0747 sec, LOAD: 1.0667 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0291 sec, LOAD: 0.8247 sec.
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0304 sec, LOAD: 0.8775 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0290 sec, LOAD: 0.5141 sec.

Package used (Python/R/Scala/Julia):
sef compiled

Build info (Required if built from source)

#!/bin/bash
set -ex
mkdir -p build && cd build
cmake \
    -DUSE_SSE=OFF \
    -DUSE_CUDA=OFF \
    -DUSE_OPENCV=ON \
    -DUSE_OPENMP=ON \
    -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
    -DCMAKE_C_COMPILER_LAUNCHER=ccache \
    -DCMAKE_C_COMPILER=gcc-5 \
    -DCMAKE_CXX_COMPILER=g++-5 \
    -DUSE_MKL_IF_AVAILABLE=OFF \
    -DUSE_SIGNAL_HANDLER=ON \
    -DCMAKE_BUILD_TYPE=Debug \
    -GNinja ..
ninja -j1

MXNet commit hash:
64657c2

Error Message:

[  PASSED  ] 80 tests.
[  FAILED  ] 2 tests, listed below:
[  FAILED  ] ACTIVATION_PERF.ExecuteBidirectional
[  FAILED  ] ACTIVATION_PERF.TimingCPU

[ RUN      ] ACTIVATION_PERF.ExecuteBidirectional
unknown file: Failure
C++ exception with description "[00:14:32] ../src/operator/nn/./activation-inl.h:207: Check failed: inputs.size() == softsign ? 3U : 2U (3 vs. 2) 

Stack trace returned 10 entries:
[bt] (0) tests/mxnet_unit_tests(dmlc::StackTrace[abi:cxx11](unsigned int)+0x63) [0x13939f8]
[bt] (1) tests/mxnet_unit_tests(dmlc::LogMessageFatal::~LogMessageFatal()+0x2f) [0x1393c60]
[bt] (2) tests/mxnet_unit_tests(void mxnet::op::ActivationGradCompute<mshadow::cpu>(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::v
ector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0xcb) [0x4665ec4]
[bt] (3) tests/mxnet_unit_tests(std::_Function_handler<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType,
 std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&), void (*)(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::alloc
ator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::_M_invoke(std::_Any_data const&, nn
vm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::
TBlob, std::allocator<mxnet::TBlob> > const&)+0x4d) [0x1757386]
[bt] (4) tests/mxnet_unit_tests(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::all
ocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::operator()(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<m
xnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&) const+0x5d) [0x13a016a]
[bt] (5) tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::Execute()+0x14f) [0x13a47a0]
[bt] (6) tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::ExecuteBackward()+0x14f) [0x13a4b7c]
[bt] (7) tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::backward(unsigned int)+0x99) [0x13bac0a]
[bt] (8) tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunGenericOperatorBackward(mxnet::test::op::OpInfo<mxnet::test::op
::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >*, unsigned int)+0xa9) [0x13ad7ae]
[bt] (9) tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunBidirectional(bool, std::vector<nnvm::TShape, std::allocator<nn
vm::TShape> > const&, std::vector<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >
 >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > > const&, 
unsigned int)+0x5b) [0x13a4db8]

Minimum reproducible example

(mxnet_py3) piotr@bananapipro:0:~/devel/mxnet (master)+$ build/tests/mxnet_unit_tests --gtest_filter="ACTIVATION_PERF.ExecuteBidirectional"

Note: Google Test filter = ACTIVATION_PERF.ExecuteBidirectional
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from ACTIVATION_PERF
[ RUN      ] ACTIVATION_PERF.ExecuteBidirectional
unknown file: Failure
C++ exception with description "[09:30:57] ../src/operator/nn/./activation-inl.h:207: Check failed: inputs.size() == softsign ? 3U : 2U (3 vs. 2) 

Stack trace returned 10 entries:
[bt] (0) build/tests/mxnet_unit_tests(dmlc::StackTrace[abi:cxx11](unsigned int)+0x63) [0x13939f8]
[bt] (1) build/tests/mxnet_unit_tests(dmlc::LogMessageFatal::~LogMessageFatal()+0x2f) [0x1393c60]
[bt] (2) build/tests/mxnet_unit_tests(void mxnet::op::ActivationGradCompute<mshadow::cpu>(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0xcb) [0x4665ec4]
[bt] (3) build/tests/mxnet_unit_tests(std::_Function_handler<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&), void (*)(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::_M_invoke(std::_Any_data const&, nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0x4d) [0x1757386]
[bt] (4) build/tests/mxnet_unit_tests(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::operator()(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&) const+0x5d) [0x13a016a]
[bt] (5) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::Execute()+0x14f) [0x13a47a0]
[bt] (6) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::ExecuteBackward()+0x14f) [0x13a4b7c]
[bt] (7) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::backward(unsigned int)+0x99) [0x13bac0a]
[bt] (8) build/tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunGenericOperatorBackward(mxnet::test::op::OpInfo<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >*, unsigned int)+0xa9) [0x13ad7ae]
[bt] (9) build/tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunBidirectional(bool, std::vector<nnvm::TShape, std::allocator<nnvm::TShape> > const&, std::vector<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > > const&, unsigned int)+0x5b) [0x13a4db8]

" thrown in the test body.
[  FAILED  ] ACTIVATION_PERF.ExecuteBidirectional (294 ms)
[----------] 1 test from ACTIVATION_PERF (294 ms total)

[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (296 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] ACTIVATION_PERF.ExecuteBidirectional

 1 FAILED TEST

(mxnet_py3) piotr@bananapipro:1:~/devel/mxnet (master)+$ build/tests/mxnet_unit_tests --gtest_filter="ACTIVATION_PERF.TimingCPU"

Note: Google Test filter = ACTIVATION_PERF.TimingCPU
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from ACTIVATION_PERF
[ RUN      ] ACTIVATION_PERF.TimingCPU
unknown file: Failure
C++ exception with description "[09:31:32] ../src/operator/nn/./activation-inl.h:207: Check failed: inputs.size() == softsign ? 3U : 2U (3 vs. 2) 

Stack trace returned 10 entries:
[bt] (0) build/tests/mxnet_unit_tests(dmlc::StackTrace[abi:cxx11](unsigned int)+0x63) [0x13939f8]
[bt] (1) build/tests/mxnet_unit_tests(dmlc::LogMessageFatal::~LogMessageFatal()+0x2f) [0x1393c60]
[bt] (2) build/tests/mxnet_unit_tests(void mxnet::op::ActivationGradCompute<mshadow::cpu>(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0xcb) [0x4665ec4]
[bt] (3) build/tests/mxnet_unit_tests(std::_Function_handler<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&), void (*)(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::_M_invoke(std::_Any_data const&, nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0x4d) [0x1757386]
[bt] (4) build/tests/mxnet_unit_tests(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)>::operator()(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&) const+0x5d) [0x13a016a]
[bt] (5) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::Execute()+0x14f) [0x13a47a0]
[bt] (6) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::ExecuteBackward()+0x14f) [0x13a4b7c]
[bt] (7) build/tests/mxnet_unit_tests(mxnet::test::op::CoreOpExecutor<float, float>::backward(unsigned int)+0x99) [0x13bac0a]
[bt] (8) build/tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunGenericOperatorBackward(mxnet::test::op::OpInfo<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >*, unsigned int)+0xa9) [0x13ad7ae]
[bt] (9) build/tests/mxnet_unit_tests(mxnet::test::OperatorRunner<mxnet::test::op::CoreOpProp, mxnet::test::op::CoreOpExecutor<float, float> >::RunBidirectional(bool, std::vector<nnvm::TShape, std::allocator<nnvm::TShape> > const&, std::vector<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > > const&, unsigned int)+0x5b) [0x13a4db8]

" thrown in the test body.
[  FAILED  ] ACTIVATION_PERF.TimingCPU (385 ms)
[----------] 1 test from ACTIVATION_PERF (386 ms total)

[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (388 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] ACTIVATION_PERF.TimingCPU

 1 FAILED TEST

Steps to reproduce

Can be reproduced in QEMU:

ci/build.py -p armv7
ci/build.py -p test.arm_qemu -b && docker run -p2222:2222 -ti mxnetci/build.test.arm_qemu

# In another terminal
rsync -e 'ssh -p2222' -vaP build/mxnet-1.3.1-py2.py3-none-any.whl build/tests/mxnet_unit_tests qemu@localhost:
ssh -p2222 qemu@localhost
$ ./mxnet_unit_tests --gtest_filter="ACTIVATION_PERF.ExecuteBidirectional"

The text was updated successfully, but these errors were encountered:

larroy · 2018-11-20T09:34:42Z

@mxnet-label-bot labels [Bug,Test,Arm,C++]

larroy · 2018-11-20T14:03:26Z

The problem is actually not arm specific, this is happening when not compiling on GPU and not MKL, we are not running those tests in CI.

lebeg · 2018-11-20T14:05:24Z

Maybe rename and edit the description of the issue then?

fixes apache#13333

vdantu · 2018-11-20T16:58:13Z

@mxnet-label-bot add [Bug,Test,Arm,C++]

fixes apache#13333

larroy · 2018-11-20T21:59:49Z

Could reproduce on amd64 with
cmake
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache
-DCMAKE_C_COMPILER_LAUNCHER=ccache
-DUSE_MKL_IF_AVAILABLE=OFF
-DUSE_CPP_PACKAGE=ON
-DUSE_CUDA=OFF
-DUSE_OPENMP=ON
-DUSE_OPENCV=ON
-DCMAKE_BUILD_TYPE=Debug
-GNinja ..
ninja -v

larroy · 2018-11-20T22:20:33Z

@mxnet-label-bot remove [Arm]

larroy · 2018-11-23T16:09:44Z

ElemwiseShape is asserting because the relu shape is 2, but hardcoded as 3 https://github.com/apache/incubator-mxnet/blob/master/src/operator/nn/activation.cc#L176

Introduced in this commit
b2ec05b

PR: #10847

The shape needs to be conditioned on the activation function

fixes: apache#13333

) * Provide a failing test for ReLU activation shape inference bug * Fix Activation backward shape inference fixes: #13333 * Add softsign Activation to test_gluon.py * Use activation in GPU if we are using CUDNN and not MKLDNN as it's happening right now * Don't disable MKLDNN

* Provide a failing test for ReLU activation shape inference bug * Fix Activation backward shape inference fixes: #13333 * Add softsign Activation to test_gluon.py * Don't disable MKLDNN

…ile (#13478) * updated to v1.5.0 * Bumped minor version from 1.4.0 to 1.5.0 on master * added Anirudh as maintainer for R package ... adding something useful and re-trigger PR check * Updated license file for clojure, onnx-tensorrt, gtest, R-package * Get the correct include path in pip package (#13452) * add find_include_path API * address reviewer comment * change return type from list to string * add unit test * address reviewer comment * address reviewer comment * address reviewer comment * address reviewer comment * fix include path problem in pip package * add comment * fix lint error * address reviewer comment * address reviewer comment * Use ~/.ccache as default ccache directory so is not cache is not erased on reboot (#13431) * Skip flaky test #13446 (#13480) * Rewrite dataloader with process pool, improves responsiveness and reliability (#13447) * fix recordio.py * rewrite dataloader with pool * fix batch as tuple * fix prefetching * fix pylint * picklable function * use pickle * add missing commit * Fix errors in docstrings for subgraph op; use code directive (#13463) * [MXNET-1158] JVM Memory Management Documentation (#13105) * update train_mnist * Add documentation for JVM Memory Management * update doc * address nit picks * address nit picks * Grammar and clarity edits for memory management doc * Edits for scala memory management * Update memory-management.md * Update memory-management.md * Update memory-management.md * capitalization fix * Update row_sparse tutorial (#13414) Update row_sparse tutorial * Add resiliency to onnx export code (#13426) * Added resiliency to onnx export code - With previous infer-shape implementation, if input shape was list instead of tuple or if extra non-existent parameters were provided, the code would still work. The fixes in this commit make sure that behavior is restored to prevent any compatibility issues with existing export code. * Fixed name of net in unittest * Fix pylint * [MXNET-1185] Support large array in several operators (part 1) (#13418) * fix a few operators with large arrays (# of elements) * fix bug in broadcast_div and add tests * address reviewer comment * add unit test * add empty line * retrigger CI * [MXNET-1210 ] Gluon Audio - Example (#13325) * Initialized the example * Addressed PR comments, about existing synset.txt file - no overwrite * RST - docstring issues fixed * added README * Addressed PR comments * Addressed PR comments, checking Divide by 0 * Raising error if format is not supported. * changed a line for ndarray of labels * Trigger CI * Trigger CI * PR comments addressed around skip_header argument * Addressed PR comments around librosa import * PR Comments * Passing lazy=lazy from argument * Added PR comments, labels to README.MD * Trigger CI * Addressing PR Comments in README * Modified README.md * Added example under audio folder * Retrigger CI * Retrigger CI * ONNX export: Instance normalization, Shape (#12920) * ONNX import/export: Make backend_rep common * ONNX export: Instance Normalization * ONNX export: Shape operator * Clarify dependency on OpenCV in CNN Visualization tutorial. (#13495) * clarify ops faq regarding docs strings (#13492) * Add graph_compact operator. (#13436) * add graph_compact. * fix. * add doc. * add tests for graph_compact. * address comments. * update docs. * trigger CI * Deprecate Jenkinsfile (#13474) * update github location for sampled_block.py (#13508) Updated to https://github.com/dmlc/gluon-nlp/blob/master/src/gluonnlp/model/sampled_block.py * #13453 [Clojure] - Add Spec Validations to the Optimizer namespace (#13499) * ONNX export: Logical operators (#12852) * Fix cmake options parsing in dev_menu (#13458) Add GPU+MKLDNN unittests to dev_menu * Revert "Manually track num_max_thread (#12380)" (#13501) This reverts commit 7541021. * Feature/mkldnn static 2 (#13503) * build mkldnn as static lib * update makefile to statically build mkldnn * build static mkldnn * fix static name * fix static name * update static for mac * rename mkldnn dep in ci * remove moving mkldnn dynamic lib * remove commented code * remove mkldnn dnaymic for unitest * force static for mkldnn lib * remove dynamic mkldnn bind * only link windows * add mkldnn.mk * try force linking * remove mkldnn dynanmic check * remove test mkldnn install * fix spacing * fix index * add artifacts * add comment about windows * remove static * update makefile * fix toctree Sphinx errors (#13489) * fix toctree errors * nudging file for CI * Disabled flaky test test_gluon_data.test_recordimage_dataset_with_data_loader_multiworker (#13527) * [MXNET-1234] Fix shape inference problems in Activation backward (#13409) * Provide a failing test for ReLU activation shape inference bug * Fix Activation backward shape inference fixes: #13333 * Add softsign Activation to test_gluon.py * Use activation in GPU if we are using CUDNN and not MKLDNN as it's happening right now * Don't disable MKLDNN

…che#13409) * Provide a failing test for ReLU activation shape inference bug * Fix Activation backward shape inference fixes: apache#13333 * Add softsign Activation to test_gluon.py * Use activation in GPU if we are using CUDNN and not MKLDNN as it's happening right now * Don't disable MKLDNN

…ile (apache#13478) * updated to v1.5.0 * Bumped minor version from 1.4.0 to 1.5.0 on master * added Anirudh as maintainer for R package ... adding something useful and re-trigger PR check * Updated license file for clojure, onnx-tensorrt, gtest, R-package * Get the correct include path in pip package (apache#13452) * add find_include_path API * address reviewer comment * change return type from list to string * add unit test * address reviewer comment * address reviewer comment * address reviewer comment * address reviewer comment * fix include path problem in pip package * add comment * fix lint error * address reviewer comment * address reviewer comment * Use ~/.ccache as default ccache directory so is not cache is not erased on reboot (apache#13431) * Skip flaky test apache#13446 (apache#13480) * Rewrite dataloader with process pool, improves responsiveness and reliability (apache#13447) * fix recordio.py * rewrite dataloader with pool * fix batch as tuple * fix prefetching * fix pylint * picklable function * use pickle * add missing commit * Fix errors in docstrings for subgraph op; use code directive (apache#13463) * [MXNET-1158] JVM Memory Management Documentation (apache#13105) * update train_mnist * Add documentation for JVM Memory Management * update doc * address nit picks * address nit picks * Grammar and clarity edits for memory management doc * Edits for scala memory management * Update memory-management.md * Update memory-management.md * Update memory-management.md * capitalization fix * Update row_sparse tutorial (apache#13414) Update row_sparse tutorial * Add resiliency to onnx export code (apache#13426) * Added resiliency to onnx export code - With previous infer-shape implementation, if input shape was list instead of tuple or if extra non-existent parameters were provided, the code would still work. The fixes in this commit make sure that behavior is restored to prevent any compatibility issues with existing export code. * Fixed name of net in unittest * Fix pylint * [MXNET-1185] Support large array in several operators (part 1) (apache#13418) * fix a few operators with large arrays (# of elements) * fix bug in broadcast_div and add tests * address reviewer comment * add unit test * add empty line * retrigger CI * [MXNET-1210 ] Gluon Audio - Example (apache#13325) * Initialized the example * Addressed PR comments, about existing synset.txt file - no overwrite * RST - docstring issues fixed * added README * Addressed PR comments * Addressed PR comments, checking Divide by 0 * Raising error if format is not supported. * changed a line for ndarray of labels * Trigger CI * Trigger CI * PR comments addressed around skip_header argument * Addressed PR comments around librosa import * PR Comments * Passing lazy=lazy from argument * Added PR comments, labels to README.MD * Trigger CI * Addressing PR Comments in README * Modified README.md * Added example under audio folder * Retrigger CI * Retrigger CI * ONNX export: Instance normalization, Shape (apache#12920) * ONNX import/export: Make backend_rep common * ONNX export: Instance Normalization * ONNX export: Shape operator * Clarify dependency on OpenCV in CNN Visualization tutorial. (apache#13495) * clarify ops faq regarding docs strings (apache#13492) * Add graph_compact operator. (apache#13436) * add graph_compact. * fix. * add doc. * add tests for graph_compact. * address comments. * update docs. * trigger CI * Deprecate Jenkinsfile (apache#13474) * update github location for sampled_block.py (apache#13508) Updated to https://github.com/dmlc/gluon-nlp/blob/master/src/gluonnlp/model/sampled_block.py * apache#13453 [Clojure] - Add Spec Validations to the Optimizer namespace (apache#13499) * ONNX export: Logical operators (apache#12852) * Fix cmake options parsing in dev_menu (apache#13458) Add GPU+MKLDNN unittests to dev_menu * Revert "Manually track num_max_thread (apache#12380)" (apache#13501) This reverts commit 7541021. * Feature/mkldnn static 2 (apache#13503) * build mkldnn as static lib * update makefile to statically build mkldnn * build static mkldnn * fix static name * fix static name * update static for mac * rename mkldnn dep in ci * remove moving mkldnn dynamic lib * remove commented code * remove mkldnn dnaymic for unitest * force static for mkldnn lib * remove dynamic mkldnn bind * only link windows * add mkldnn.mk * try force linking * remove mkldnn dynanmic check * remove test mkldnn install * fix spacing * fix index * add artifacts * add comment about windows * remove static * update makefile * fix toctree Sphinx errors (apache#13489) * fix toctree errors * nudging file for CI * Disabled flaky test test_gluon_data.test_recordimage_dataset_with_data_loader_multiworker (apache#13527) * [MXNET-1234] Fix shape inference problems in Activation backward (apache#13409) * Provide a failing test for ReLU activation shape inference bug * Fix Activation backward shape inference fixes: apache#13333 * Add softsign Activation to test_gluon.py * Use activation in GPU if we are using CUDNN and not MKLDNN as it's happening right now * Don't disable MKLDNN

larroy added a commit to larroy/mxnet that referenced this issue Nov 20, 2018

fix ActivationGradCompute on CPU

6789f9f

fixes apache#13333

larroy mentioned this issue Nov 20, 2018

fix ActivationGradCompute on CPU (had an assertion when not on GPU & MKL) #13340

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marcoabreu added ARM Bug C++ Related to C++ Test labels Nov 20, 2018

larroy added a commit to larroy/mxnet that referenced this issue Nov 20, 2018

fix ActivationGradCompute on CPU

66f44e4

fixes apache#13333

larroy changed the title ~~Two C++ unit test failing on ARMv7 ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU~~ Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU Nov 20, 2018

marcoabreu removed the ARM label Nov 20, 2018

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

7b702fc

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

7ec2ee6

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

e3e5973

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

c03d0ef

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

33b436c

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 27, 2018

Fix Activation backward shape inference

9f404f3

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 28, 2018

Fix Activation backward shape inference

520ac76

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 29, 2018

Fix Activation backward shape inference

a2f2d44

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Nov 30, 2018

Fix Activation backward shape inference

612a206

fixes: apache#13333

This was referenced Dec 3, 2018

[MXNET-1234] Fix shape inference problems in Activation backward #13409

Merged

[v1.4.x][MXNET-1234] Port of #13409 to the release branch #13487

Merged

larroy added a commit to larroy/mxnet that referenced this issue Dec 3, 2018

Fix Activation backward shape inference

c91b944

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Dec 3, 2018

Fix Activation backward shape inference

bf2e6ae

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Dec 3, 2018

Fix Activation backward shape inference

e74f796

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Dec 3, 2018

Fix Activation backward shape inference

d91a85a

fixes: apache#13333

larroy added a commit to larroy/mxnet that referenced this issue Dec 4, 2018

Fix Activation backward shape inference

f2b85a4

fixes: apache#13333

eric-haibin-lin closed this as completed in #13409 Dec 4, 2018

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Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU #13333

Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU #13333

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larroy commented Nov 23, 2018

Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU #13333

Two C++ unit test failing ACTIVATION_PERF.ExecuteBidirectional ACTIVATION_PERF.TimingCPU #13333

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larroy commented Nov 20, 2018

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