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Patch 1 #1
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…t-form representation (apache#13259)
* patch fix * update ignore * rename getContext to bindToDevice * Update JavaBenchmark.java
* 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
* Addressing PR feedback for merging Java API into master * Changed constructors to package private instead of private
* adding unit test for MKLDNN FullyConnected operator * removing mkldnn filter * removing mkldnn filter
* fix. * add test. * retrigger
* Addressed doc issues * Update optimizer.py
…structions (apache#13267) * Added command line alternative to IntelliJ * Removed the duplicate file * Fixed typos * Fixed minor command issue
* 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
* 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
* 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
* Fix Sphinx python docstring formatting error (apache#13021). Fixes apache#13021 * Update src/operator/nn/batch_norm.cc Co-Authored-By: frankfliu <[email protected]>
* merge NEWS.md from 1.4.x to master * NEWS.md backport from v1.4.x to master
…e#13599) * fallback to dense version for grad(reshape), grad(expand_dims) * add _backward_reshape gpu version * reshape test case comments * fix gpu test * remove mkldnn support for _backward_reshape
* Add Flatten before Gemm * ONNX export test: Allow multiple inputs in forward pass * ONNX export: Test for fully connected
…che#12977) * Adding cpp-package directory to the Doxyfile. Updating the index.md file in c++ api directory. * Updating the link to classes in C++ API to point to correct html file. * Updated the links to use relative paths. * Removed the extra slash character in the url * Excluded the 3rdparty folder as per the review comment.
* Added timeout/retry (linear backoff) to docker cache download * Units changed, as time.sleep takes seconds as argument * Improved error handling * Using retry decorator * Added retry decorator to _login_dockerhub method * Fixed wrong import
* Update test_gluon_trainer.py * Update test_gluon_trainer.py * test
* fp16 dot * update mshadow * update mshadow * update mshadow
* fix the quantization script to support python2 * Fix comments, fix similiar issue in imagenet_inference.py
* ONNX test code cleanup * Make tests use the common test case list * Remove import test_cases * Make Gluon backend rep common * Partially enable broadcast tests * Common function to populate tests * Make backend common * test models * Test nodes * ONNX export: Test for fully connected * Edit CI scripts mxnet export test cleanup * Further cleanup backend tests * README * Some corrections * test case format for test_models
* Port of scala infer package to clojure * Add inference examples * Fix project.clj * Update code for integration tests * Address comments and add unit tests * Add specs and simplify interface * Minor nit * Update README
…3728) * tests * remove optimizer and move op to contrib * rename parameter
…e#13654) * Logsoftmax, missing tests * Support multiple outputs in Gluon backendrep * Remove repeated unsqueeze test * Allow multiple output support
* Common test caller * Remove incorrect comment * Make corrections to CI * fix ci script
* ONNX import: Hardmax * Fix lint errors * add github link for issue with reshape
* add clarification for param_dict * more tests for dist kvstore * more unittests * fix a bug * more dist exception test * revert optimizer list * fix bug and comment * fix doc rendering and lint * add invalid sched test * fix website * trigger * update doc
* Reorder module import orders for dist-kvstore * more code comments
* Allow CMake based installation of cpp-package * Add installation of missing nnvm headers * Add documentation as to where public headers will be installed
https://github.com/apache/incubator-mxnet/blob/a38278ddebfcc9459d64237086cd7977ec20c70e/example/image-classification/train_imagenet.py#L42 When I try to train imagenet with this line commented, the train-accuracy reaches 99% while the validation-accuracy is only less than 50% (single machine, 8 GPUs, global batchsize=2048, Resnet50). Absolutely this is overfitting. Then I uncomment this line and try again with the same experiment settings. This time both train and validation accuracy converge to about 70%. Thus, it seems that this data augmentation is pretty important for ImageNet training. Perhaps it will be better to uncomment this as default, so that future developers won't get confused by the over-fit issue.
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