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merge upstream to resolve use_mkldnn issue #557
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* Fix exception handling api doc * Update waitall api doc Co-Authored-By: anirudh2290 <anirudh2290@apache.org>
* add inception test * fix max iter for mlp * rename and add comment * rename epoch num
* Add imresize API to docs * address comments * copyMakeBorder
* fix control_flow_op * change type for M * add test for sparse where op
* add mkl blas to Jenkins * add mkl install script * fix bug in mkl script * remove python2 ut and add cpu-mkl node
Merge this PR for 1.4.x
* [MXNET-1155] Add scala packageTest utility * Clean up utility * Safe change directory in Makefile for scala * mvn install file instructions with details
Major JNI feature changes. Please find more info here: https://cwiki.apache.org/confluence/display/MXNET/Scala+maven+build+improvement
* Always use config.mk in make install instructions * Specify Cuda 0 for ubuntu with mkldnn * Scala install doc avoid build_from_source Minor doc fixes * Fix build_from_source CMake usage * CPP Install Instruction with CMake * Use cmake out of source build
* Optimize C++ API Pass parameter with reference instead of value. Add const as well as it is not changed. * fix docs/architecture/overview.md Fix BinaryShapeFunction typedef Add a right brace for SmoothL1Shape_
…ed in the model (#13596)
* openblas script * ps-lite dependencies * USE_S3 dependencies * image libraries * license
* add batch norm test * fix formatting * use out_arr as input * fix typo * remove const * use ptr * eval ptr
* Fix the bug of BidirectionalCell I did hybridize( ) and pass "valid_length" to the unroll( ) function of BidirectionalCell, then returned AssertionError in line 79. Because symbol.split( ) return a symbol but not a symbol list. Result in the length of inputs dont equal parameter "length" when call unroll( ) to compute r_outputs and r_states. * add a test for BidirectionalCell * Fix the bug of BidirectionalCell I did hybridize( ) and pass "valid_length" to the unroll( ) function of BidirectionalCell, then returned AssertionError in line 79. Because symbol.split( ) return a symbol but not a symbol list. Result in the length of inputs dont equal parameter "length" when call unroll( ) to compute r_outputs and r_states. * fix test_bidirectional_unroll_valid_length( ) Fix the error of parameter. * Fix the bug of BidirectionalCell I did hybridize( ) and pass "valid_length" to the unroll( ) function of BidirectionalCell, then returned AssertionError in line 79. Because symbol.split( ) return a symbol but not a symbol list. Result in the length of inputs dont equal parameter "length" when call unroll( ) to compute r_outputs and r_states. * fix test_bidirectional_unroll_valid_length( )
* Revert "Revert "Feature/mkldnn static 2 (#13503)" (#13540)" This reverts commit a3eca5f. * include headers on mkldnn lib * retrigger * retrigger
* config for pip * symbol whitelist * maven build config
…13602) * apache/mxnet#12255 doing import mxnet in multiple processes take very long time. Details : #12255 One of the reason we have OMP tuning code which iterates to find OMP tune overhead. We are reducing this iteration count to reduce the overehead of tuning code. Also, We added an environment variable where users can set the number of cores that should be used to determine tuning. * cpplint fix * Adding new environment variable: MXNET_USE_NUM_CORES_OPERATOR_TUNING to doc * fixing formatting in doc
* Add reshape op supported by MKL-DNN * fix build issue * fix lint * fix lint * fix lint * fix lint * fix lint * fix lint * fix white space * add unit test * merge if blocks
* Improve dev_menu, add build command and virtualenv creation with local builds for easy testing * Update dev_menu.py Co-Authored-By: larroy <pedro.larroy.lists@gmail.com> * Cuda off by default, use ccache * address CR
…e latest maven.org release (#13507) * Correct the versions so they correspond to the latest maven.org release * trigger build * feedback from @kohr-h
* Change argsort to argpartition * Global statistics in metrics * Fix lint * Fixes from review * Trigger * Fixes from review, fix to F1, MCC and perplexity metrics, added test for global stats * Fix lint * Fix compatibility with Python 2
This reverts commit 5bcf2bd.
* support mkl log when dtype is fp32 or fp64 * remove macro * ensure data size less than or equal MKL_INT_MAX * code specification * fix indent * for retrigger
* update the scala installation tutorial on intellij * update the so answer * update the so answer
* Add CPU implementation of ToTensor * Add tests for cpu * Add gpu implementation and tests * Fix lint issues * Cleanup includes * Move back changes to original image operators files * Add 4D example * resolve merge conflicts * Fix failing tests * parallelize on channel in kernel launch
ran 10000 times with no failures
* Fix doc building * Remove deplicate in
* Add resource scope to clojure package * add rat * fix integration test * feedback from @benkamphaus - move from defs to atoms to make the tests a bit better * adding alias with-do and with-let more tests * another test * Add examples in docstring * refactor example and test to use resource-scope/with-let * fix tests and problem with laziness now they work as expected! * refactor to be a bit more modular * remove comments
* add new cloud providers * fix colon
* cudnn dropout * test dropout as stateful op * add cudnn_off * refactor * fix bug when using inf forward * turn on cudnn in gluon * reuse dropout state space * dropout passthrough * address comments
* keeping same contexts for comparison * enabling test * testing default context * Revert "testing default context" This reverts commit 1f95d0228178debde14680839bb6abab14c6d049. * Disabling test due to CI failure on MKL-DNN
* Expand,tile op export * fix * adding test cases * adding comments
* fix roi align test * retrigger unittest * add more test detail for ROIAlign test * remove url in test_op_roi_align * remove blank line in test_op_roi_align in test_operator * merge master * Update test_operator.py * retrigger CI
* parallelize on channel forward pass * parallelize on channel normalize backward pass * Fix lint issues * Trying to fix CI build failure on GPU * Fix failing GPU test on CI Do not pass normalize param as is to GPU kernel * Fix to_tensor tests * Pass mean and std_dev as native types for kernel * Fix CI failure. Do not pass mean, std as vector to kernel
* Better bulkappend * Fix lint
* updating scala docs * Addressed PR feedback
…(#13680) * [MXNET-1121] Example to demonstrate the inference workflow using RNN * Addressed the review comments. Updated the ReadMe files. * Removed the unnecessary creation of NDArray * Added the unit tests to nightly tests to catch the failure. * Updated the makefiles and unit tests so that the examples are built and tested in nightly * Added the visual representation of the model and fixed the CI failure. * Added the missing pdf file. * Fixing the broken ci_test.sh * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/README.md Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Update cpp-package/example/inference/simple_rnn.cpp Co-Authored-By: leleamol <19983848+leleamol@users.noreply.github.com> * Applying unresolved changes to README file. * Fixing the CI build failure. * Updated the RNN example from sequence generation to sentiment analysis * Updated the readme files. Updated the example to use trained model and updated the unit test. * Addressed the review comment to increase the default sequence length. Added the examples with inputs of various lengths. * Updated the example to handle variable length input. Updated the readme and unit test files accordingly. * Updated the example to share the memory between executors by createing shared executors. * Updated the creation of executors from largest to smallest bucket key * Creating the executor for the highest bucket key. * Updated the unit test to check for the results in a range and modified the function name to be consistent with others. * Fixed the logic to find the right bucket.
* hybridize rnn and add model graph * trigger CI * separate mxboard visualization * add options and she-bang * add defaults * trigger CI * rename export-model
* exclude concat for gpu quantization * remove quantized_concat test in non-subgraph flow
* Remove stale check for op req type * Do not register to tensor operator with in place option.
* Enable s8s8 support for MKLDNN convolution. * Fix cpp build * Fix build. * Fix build * Remove openmp min/max reduction for windows build * Add mkldnn_OIhw4i16o4i_s8s8 support * Add all s8s8 weight format * Change ssd quantize script. * Update * Manually cast mshadow shape size to size_t * Fix merge. * Fix perl package. * Retrigger CI * Fix GPU test * Fix GPU test * Rerun CI * Rerun CI * Rerun CI * Rerun CI * Remove weight_channelwise_scale from params. * Fix * Keep API compatible. * Rerun CI * Rerun CI * Rerun CI * Rerun CI * Address comments. * fix. * Address debug build. * Add comment for next_impl * Rerun ci * Add new api MXExecutorSetMonitorCallbackEX * Add default value for monitor_all for cpp header. * Rerun CI * fix * script change for uint8. * trigger ci * trigger ci
…815) * Unify the style here Unify the style here and remove the testing 'print' code segment. * Unify the description of comment Change the description of comment from "multi-layer perceptron" to "Get multi-layer perceptron" * Unify the style of comments Unify the style of comments suggested by @sandeep-krishnamurthy * git pull the lastest code from master of incubator-mxnet * Complete rebase * Solve PEP8 [C0304 ] Final newline missing Sovle example/deep-embedded-clustering/solver.py(150): [C0304 ] Final newline missing
mbrookhart
approved these changes
Feb 12, 2019
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