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fix TimeseriesGenerator's glitch mentioned in #9778 #9899

Merged
merged 1 commit into from
Apr 14, 2018
Merged

fix TimeseriesGenerator's glitch mentioned in #9778 #9899

merged 1 commit into from
Apr 14, 2018

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lucasdavid
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This PR fixes the TimeseriesGenerator's glitch that was mentioned in #9778, where the last sample wasn't being included in the generated series.
It also adds a validation step in __init__ to prevent this non-informative error:

>>> x = np.arange(10)
>>> g = TimeseriesGenerator(x, x, 10, batch_size=1)
>>> print(len(g))
ValueError: __len__() should return >= 0

@lucasdavid lucasdavid force-pushed the fix-time-series-generator branch 3 times, most recently from 705392e to 17e0ca5 Compare April 11, 2018 12:04
@lucasdavid lucasdavid changed the title updates #9778 fix TimeseriesGenerator's glitch mentioned in #9778 Apr 11, 2018
fchollet
fchollet reviewed Apr 11, 2018
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Thanks for the PR!

keras/preprocessing/sequence.py
@@ -326,9 +326,15 @@ def __init__(self, data, targets, length,
self.reverse = reverse
self.batch_size = batch_size

if self.start_index > self.end_index:
raise ValueError('`start_index+length=%i > end_index=%i` '
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This should read self.start_index, not self.start_index+length

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self.start_index is set to start_index + length a few lines above, so the generator never picks a index that doesn't have sufficient previous steps to fill in the memory buffer.
I could've written self.start_index, but I thought it would be more informative to do it like this because the users will only have access to start_index and length parameters. Should I change it anyway?

tests/keras/preprocessing/sequence_test.py Outdated
expected = max(0, len(x) - length)
actual = len(g)

assert expected == actual, \
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You don't need this error message since it's a unit test. If you prefer including it, please format without the use of \ to follow codebase style

tests/keras/preprocessing/sequence_test.py Outdated
actual_sequences = sum(len(_y) for _y in y)
actual_batches = len(y)

assert expected_sequences == actual_sequences, \
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Same comment here and below

@lucasdavid lucasdavid force-pushed the fix-time-series-generator branch from 17e0ca5 to 9ce8fe5 Compare April 11, 2018 22:11
@lucasdavid lucasdavid force-pushed the fix-time-series-generator branch from 9ce8fe5 to b424ae1 Compare April 11, 2018 23:17
fchollet
fchollet approved these changes Apr 14, 2018
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LGTM, thanks!

@fchollet fchollet merged commit 5422fdd into keras-team:master Apr 14, 2018
@lucasdavid lucasdavid deleted the fix-time-series-generator branch April 16, 2018 12:26
dschwertfeger added a commit to dschwertfeger/keras that referenced this pull request Apr 25, 2018
@dschwertfeger
Merge remote-tracking branch 'upstream/master' into tensorboard-callb…
f116bc1 
…ack-embeddings-from-layer-outputs

* upstream/master: (34 commits)
  Refactor training part of `engine` module. (keras-team#10029)
  Fix Bidirectional Regularization (keras-team#10012)
  Refactor topological part of `engine` module (keras-team#10023)
  Add `separable_conv2d` for Theano (keras-team#10003)
  fixing typos (keras-team#10016)
  Prepare 2.1.6 release.
  Add tutorial link in docs.
  Sync docstring of preprocess_input with _preprocess_numpy_input and
_preprocess_symbolic_input in imagenet_utils.py (keras-team#10006)
  Immigrate reference operations to a separate module (keras-team#9948)
  Chenta/cntk bn (keras-team#9952)
  Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)
  Exclude multi-gpu utils when reporting coverages (keras-team#9942)
  Allow shift_range to be 1-D array-like or int (keras-team#8869)
  Fix PEP8
  Added an error message for undefined shape on NASNet. (keras-team#9891)
  fix TimeSeriesGenerator glitch (keras-team#9899)
  Updated for TF 1.7 (keras-team#9937)
  Add support for `constants` in Bidirectional wrapper (keras-team#9260)
  Added note to manually install h5py where needed (keras-team#9830)
  Fix stateful metrics when passing dict to compile (keras-team#9894)
  ...
Vijayabhaskar96 pushed a commit to Vijayabhaskar96/keras that referenced this pull request May 3, 2018
@Vijayabhaskar96
fix TimeSeriesGenerator glitch (keras-team#9899)
6bf441f
sandeep-krishnamurthy pushed a commit to awslabs/keras-apache-mxnet that referenced this pull request May 17, 2018
@roywei @sandeep-krishnamurthy
Rebase to latest Keras April 20 2018 (#71)
865d005 
* Improve tests by designating dtype of sample data (keras-team#9834)

* Document that "same" is inconsistent across backends with strides!=1 (keras-team#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* keras-team#9642 Add kwarg and documentation for dilation_rate to SeparableConvs (keras-team#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (keras-team#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (keras-team#9866)

* Fix image_ocr.py example ValueError (keras-team#9869)

* Fixed the NASNet issue. (keras-team#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (keras-team#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (keras-team#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (keras-team#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (keras-team#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (keras-team#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (keras-team#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (keras-team#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (keras-team#9920)

* Fix `batch_dot` of CNTK when `axes=None` (keras-team#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (keras-team#9922)

* Fix stateful metrics when passing dict to compile (keras-team#9894)

* Added note to manually install h5py where needed (keras-team#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (keras-team#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with keras-team#8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (keras-team#9937)

* fix TimeSeriesGenerator glitch (keras-team#9899)

* Added an error message for undefined shape on NASNet. (keras-team#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (keras-team#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (keras-team#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)

* Chenta/cntk bn (keras-team#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (keras-team#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* add multi gpu model example (#85)

* add multi gpu model

* specify param name

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings
roywei added a commit to awslabs/keras-apache-mxnet that referenced this pull request May 18, 2018
@roywei
Keras MXNet 2.1.6 Release (#101)
4857329 
* Improve tests by designating dtype of sample data (keras-team#9834)

* Document that "same" is inconsistent across backends with strides!=1 (keras-team#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* keras-team#9642 Add kwarg and documentation for dilation_rate to SeparableConvs (keras-team#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (keras-team#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (keras-team#9866)

* Fix image_ocr.py example ValueError (keras-team#9869)

* Fixed the NASNet issue. (keras-team#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (keras-team#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (keras-team#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (keras-team#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (keras-team#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (keras-team#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (keras-team#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (keras-team#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (keras-team#9920)

* Fix `batch_dot` of CNTK when `axes=None` (keras-team#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (keras-team#9922)

* Fix stateful metrics when passing dict to compile (keras-team#9894)

* Added note to manually install h5py where needed (keras-team#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (keras-team#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with keras-team#8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (keras-team#9937)

* fix TimeSeriesGenerator glitch (keras-team#9899)

* Added an error message for undefined shape on NASNet. (keras-team#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (keras-team#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (keras-team#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)

* Chenta/cntk bn (keras-team#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (keras-team#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* add multi gpu model example (#85)

* add multi gpu model

* specify param name

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings

* Update CNN benchmark result (#97)

* update benchmark numbers

* update number

* update result

* Update RNN benchmark results (#98)

* Fix pep failures

* Add 8 GPUs RNN benchmark results

* remove checking data format (#102)

* update imagenet result (#103)
sandeep-krishnamurthy pushed a commit to awslabs/keras-apache-mxnet that referenced this pull request Jun 15, 2018
@roywei @sandeep-krishnamurthy
Rebase to latest Keras April 20 2018 (#71)
045969d 
* Improve tests by designating dtype of sample data (keras-team#9834)

* Document that "same" is inconsistent across backends with strides!=1 (keras-team#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* keras-team#9642 Add kwarg and documentation for dilation_rate to SeparableConvs (keras-team#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (keras-team#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (keras-team#9866)

* Fix image_ocr.py example ValueError (keras-team#9869)

* Fixed the NASNet issue. (keras-team#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (keras-team#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (keras-team#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (keras-team#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (keras-team#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (keras-team#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (keras-team#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (keras-team#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (keras-team#9920)

* Fix `batch_dot` of CNTK when `axes=None` (keras-team#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (keras-team#9922)

* Fix stateful metrics when passing dict to compile (keras-team#9894)

* Added note to manually install h5py where needed (keras-team#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (keras-team#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with keras-team#8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (keras-team#9937)

* fix TimeSeriesGenerator glitch (keras-team#9899)

* Added an error message for undefined shape on NASNet. (keras-team#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (keras-team#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (keras-team#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)

* Chenta/cntk bn (keras-team#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (keras-team#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* add multi gpu model example (#85)

* add multi gpu model

* specify param name

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings
sandeep-krishnamurthy added a commit to awslabs/keras-apache-mxnet that referenced this pull request Jun 21, 2018
@sandeep-krishnamurthy
Prepare for keras-mxnet 2.2 release (#117)
332c62f 
* Document that "same" is inconsistent across backends with strides!=1 (#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* Add h5py to dependencies

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Added note to manually install h5py where needed (#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Added an error message for undefined shape on NASNet. (#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Make conv_invalid_use and pooling_invalid_use efficient (#9944)

* Chenta/cntk bn (#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* fixing typos (#10016)

* Add `separable_conv2d` for Theano (#10003)

* Add `separable_conv2d` for Theano

* Enable the layer test for `separable_conv2d`

* Fix the strides for 1x1 conv

* Refactor topological part of `engine` module (#10023)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Fix Bidirectional Regularization (#10012)

* Fix Bidirectional Regularization

Override the Wrapper `get_updates_for` and `get_losses_for` methods so that contributions from both the forward and backward layers are included in Bidirectional.

* Use Parent for Calculating Inner Inputs

Remove unneeded inner input calculations.

* Simplify Bidirectional Losses

* Add Bidirectional Unit Tests

Test Bidirectional updates and losses.

* Remove Trailing Whitespace

* Fix Bidirectional Loss Inputs

* Add Tests for Conditional Updates/Losses

* Remove Whitespace

* Refactor training part of `engine` module. (#10029)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Fix `int_shape` of Theano and Refactor associated lines (#10030)

* Add exceptions for `batch_dot` (#10020)

* Enable Xception to work on Theano and CNTK (#10024)

* Enable Xception to work on Theano and CNTK

* Fix different predictions over all the backends

* Add support for passthrough arguments to NumpyArrayIterator (#10035)

* Add support for second output to NumpyArrayIterator

* Enable Model subclassing API (#10046)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Refactor Network to prepare support for Model subclassing

* Finish enabling Model subclassing.

* Add `long_description` field in setup.py.

* Remove unused import

* Increase pytest duration from 10 mins to 20 mins (#10072)

* [RELNOTES] Simplify implementation of Sequential and remove legacy Merge support (#10077)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Refactor Network to prepare support for Model subclassing

* Finish enabling Model subclassing.

* Simplify Sequential implementation.

RELNOTES: This breaks weight loading and model loading/saving for models from Keras 0.* that used Merge layers. The Merge layer has been deprecated for 2 years.

* [RELNOTES] Remove support for Keras 0.* Merge layer and associated functionality, which was scheduled for 08/2017.

* fix typo (#10078)

* Add documentation to several activation functions (#10066)

* Add documentation to several activation functions

* Fix style issues.

* Small style fixes.

* [RELNOTES] Introduce `preprocessing.image.save_img` and remove deprecated imsave method in neural style transfer example (#9996)

* imsave method in scipy.misc package is deprecated - now using imageio

* updated save_img method to use array_to_img method.  also updated the neural style transfer example to use the new save_img method

* forgot to commit changes - updated save_img

* added file_format and **kwargs parameter to save_img and updated docstring

* removed space at the end of a line in save_img method.  updated instances of imsave in example scripts with save_img method.

* added kwargs to docstring.  removed additional whitespace lines

* removed trailing whitespace

* Extensive style fixes in `preprocessing.image`.

* [RELNOTES] Allow loading external backends (#10034)

* load external backend

* safety++

* Excpetion -> ValueError

* Revert TF version to 1.7 on Travis CI. (#10101)

* New Callback: EarlyBaselineStopping (#10061)

* Initial Commit

* Continued changes

* Alpha version

* Added support to make sure that previous epochs, which may pass the
baseline test, are kept in variable history.

* Code formatting

* Code formatting

* Code formatting to address CI errors

* Code formatting for CI errors

* Initial unit test code

* Adjust for epoch being zero-based

* Code formatting

* Unit tests added

* Code formatting

* Code formatting

* Factorized the unit test

* Code formatting

* Refactored to be part of EarlyStopping and modified unit tests

* Code formatting

* Adds MobiletNetV2 to applications (#10047)

* [RELNOTES] Allow symbolic tensors to be fed to models (with TF backend) (#10087)

* Allow symbolic tensors to be fed to models (with TF backend)

* Skip tensor feeding tests when TF>=1.8 not available.

* [RELNOTES] Fix EarlyStopping API

* Fix shape mismatch in `rnn()` of tensorflow_backend (#10038)

* Fix shape mismatch in `rnn()` of tensorflow_backend

Fix the shape mismatch in `rnn()` with `not unroll` and `mask is not None` of the Tensorflow backend.

Problem: If the rnn cell has any (recurrent) `states[i]` whose shape is different from that of the `output` (`states[0]`), there will raise an `ValueError` when updating that state.

Reason: This is because the `tiled_mask_t` is not updated correctly for each `states[i]` but instead is simply copied from that of the `output` (`states[0]`).

Solution: Tile the `mask_t` with the correct shape of each `states[i]`. Notice that in a similar situation with `unroll is True`, the `tiled_mask_t` is handled correctly.

* add unit_test for rnn() with states whose shape is different from that of the output.

* Revert "add unit_test for rnn() with states whose shape is different from that of the output."

This reverts commit f1df2a58ff635bbf698444e3d7403785a92dfed1.

* Simplify the unit_test for rnn with additional states

* [RELNOTES] Default `Flatten` layer’s `data_format` argument to `None`.

* #10080 Convert CuDNN weights in nested Model. (#10081)

* #10080 Convert CuDNN weights in nested Model.

- similar problem to nesting in Bidirectional (#8860)
- quick fix: just copy/paste. I'll refactor it later
- also convert biases from H5 Dataset to np.array for reshape() (#9662)

* Refactor keras.engine.saving.preprocess_weights_for_loading().

- less duplication
- extracted conversion methods for Bidirectional/Model/Sequential

* Format docstrings to follow the project code style.

* Move tests of CuDNN RNN weight conversion to a more proper place.

- move from cudnn_recurrent_test.py to test_model_saving.py
- adjust imports to be consistent

* Make better tests for CuDNN RNN weight conversion.

- add nested models (#10080)
- various model types: add Model, Sequential (not only Sequential)
- convert weights on model, not layer (not test nesting in models)
  - test just by save/load model weights instead of calling preprocess_weights_for_loading() directly

* Check GPU support via tf in pytest skipif with short-circuit evaluation.

It seems that multiple skipif decorators get evaluated eagerly, not lazily.
Thus it fails on theano and cntk backends.

I don't understand why the tests didn't fail until now.
Maybe some change in pytest?

* Refactor (deduplicate) skipif decorators for TensorFlow and GPU.

At least multiple occurrences within a test module.
Now we can't import from `tests/` and `keras.utils.test_utils` don't se pytest.
Otherwise we can define the marker only once at all.

* Fix PEP8 (whitespace).

* Add `separable_conv1d` (#10125)

* Add `separable_conv1d` for Theano

* Add `separable_conv1d` for CNTK

* Fix preprocess_input not working with int arrays (#10134)

* Make MobileNet tests random (#10132)

* Sample weighted ImageDataGenerator (#10092)

* Add support for sample_weight in ImageDataGenerator.flow

* Added test for sample weighted imagedatagen

* clarified docs + PEP8

* pep8 - blank line

* sample_weight argument after shuffle

* RNN docstring fixes; pass `maximum_iteration` argument to `while_loop` in TF.

* Use `embedding_lookup` for `gather` in TF backend (enables partitioned variables).

* Add `data_format` argument to Conv1D; docstring style fixes.

* Further fixes.

* Fix initializers (#9963)

* fix VarianceScaling

* Correct standard initializer testing

* Add test for truncated normal in backend

* Use correct theano function for truncated_normal

* Fix sloppiness in correction

* fix PEP

* improve style initialiser fix

* fix line length

* Use NCW/NWC for conv1d data format in TF backend.

* Model loading: do not return inside `try` block.

* Rely on `Flatten` layer to do data_format conversion in ResNet50, VGG16, VGG19.

* Remove potentially misleading warning messages in `applications`.

* Fix typo.

* Remove useless super delegation.

* Remove batch_size when doing stepwise fit (#10144)

`batch_size` is always `None` , because `steps_per_epoch` and `batch_size` are mutually exclusive.
Passing batch_size seems irrelevant as `None` is its default value in `test_loop`

* Add exceptions for `fit_loop` (#10145)

* Style fixes (#10148)

* Fix ConvLSTM2D unit_forget_bias initializer

* Avoid a warning by using  'x = x * y' instead of 'x *= y' (#10158)

* Fix undefined behaviour: preprocess_input copying/not copying the input arrays (#10153)

* Add copy option for image preprocessing

* Fix unnecessary import

* Fix style

* fix test error

* Make modifications in-place instead

* vae examples fixes (#10062)

* vae examples fixes

* white spaces around op

* comments and docstring fixes

* comments and docstring fixes

* comments and docstring fixes

* fixes on docs

* docs and spacing

* Merge 2 functions together in applications MobileNetV2 (#10163)

* merge 2 functions together

_inverted_res_block() and _first_inverted_res_block() are nearly the same. Merged them into one function
1. skip "Expand" part for 0 block
2. made layers names similar to original TF graph names

* added "mobl_" to prefix, pep8 fix

* remove dropout parameter

* concise prefix name

* Remove named argument from schedule function (#10178)

* Add missing doc (#10188)

* Best to set self.built=True at the end of build() (#10191)

When using Keras on TensorFlow (in graph mode), via `tf.keras`, then calling `self.add_weight()` fails if `self.built==True`, so it is best to encourage users to set `self.built=True` at the *end* of their `build()` method, rather than just "somewhere".

* Clean up preprocessing of `depthwise_kernel` for Theano (#10189)

* Allow dynamic backends in _need_convert_kernel (#10111)

* Fix _need_convert_kernel for external backends

* Don't assume external backend won't support NASNet

* Update from review comments

* fix TensorBoard callback with unit test (#10173)

* Allow project specific config files in Keras (#10183)

* Allow project specific config files in Keras

* Clearer code, updated comment

* Update cifar10_resnet.py (#10199)

change the comments on line 133.

* Adds height_shift_range to preprocessing.image doc and adds support for indentation in auto-generated doc (#10194)

* Update README.me

* Mobilenetv2 explanation  (#10174)

* i add mobilenetv2 to the table

* dd explanation for mobilenetv2

* add explanation for mibilenetv2

* Make multi_gpu_model serializable.

* Skip tests for multi gpu

* Fix slice namespace collision in backend.

* Skip multi_gpu tests for other backends than TF

* Replace np.ceil() with a faster operation (#10184)

* Replace ceil() with faster a operation

Replacing np.ceil() with faster operations, as suggested in #8488

* Revert "Replace ceil() with faster a operation"

This reverts commit 74fe60b445377b4f1be1d0a36b4777d7ed4f1c1b.

* Replace np.ceil() with a faster operation

* Fix syntax error

* Remove trailing whitespace

* Explicitly mention using a Sequence object in val (#10223)

* Grammatical error - "inputs channels" rather than "input". (#10217)

* Fix duplicated argname: num_gpus === parts (#10228)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix NASNet (#10209)

* Fix NASNet

* Update weight files

* In-place split to avoid inter-device duplication (#10230)

New Benchmark by in-place split:

>> keras.application.Resnet50 224x224x3 (NCWH; NVidia Tesla P100 x 4)
 input_shape = 3x224x224, batch_size =  96 x 4: 392(images/sec) => 417(images/sec)
 input_shape = 3x299x299, batch_size =  64 x 4: 229(images/sec) => 244(images/sec)
 input_shape = 3x224x224, batch_size =   8 x 4: 148(images/sec) => 163(images/sec)

>> keras.application.InceptionV3 (NCWH; NVidia Tesla P100 x 4)
 input_shape = 3x224x224, batch_size = 128 x 4: 488(images/sec) => 526(images/sec)
 input_shape = 3x299x299, batch_size =  96 x 4: 270(images/sec) => 294(images/sec)
 input_shape = 3x224x224, batch_size =   8 x 4: 146(images/sec) => 158(images/sec)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Increase test coverages by adding invalid CNTK usecases (#10236)

* Remove Sequential.model deprecation warning (#10256)

* Remove Sequential.model deprecation warning

* Remove dead line of code

* Increase test coverages by factorizing CNTK pads (#10259)

* Refactor ImageDataGenerator (#10130)

* Create get_random_transform and refactor

* Fix style and add tests

* Add more tests

* Fix documentation error

* Fix documentation style issue

* add apply_affine_transform

* document transformation dictionary

* Doc style fix

* Remove deprecated model.model from engine/saving (#10275)

* Typo in docstring for softplus (#10277)

Softplus docstring missing a parenthesis.

* Make Dot documentation inline with Concatenate (#10271)

Doc expects a list containing 2 tensors.

* Fixes automatic doc generation problem with nested lists. Adds a new test (#10212)

* Fixes automatic doc generation problem with indented lists. Adds a new test

* Some style fixes on doc automatic generation files

* Fixes a bad space in convolutional_recurrent.py

* Changes the test_doc_auto_generation in order to include a doc string taken from the codebase. Allows text lines following nested lists

* Use count_params function for non_trainable_count. (#10280)

* load_weights will fail if shape mismatch (#10266)

Fix for #10265

* Adds to and alphabetizes documentation of Layer base class. (#10282)

* Alphabetizes and adds to layers doc.

* Responding to @cais comments

* fix spacing.  Remove in(out)bound_nodes

* Non training Batch Norm operator has bad performance for it running into tensorflow's non fused batch norm API (#10207)

* When use tensorflow as backend, let batch norm run into fused batch norm as much as possible, which has better performance.

fix issue: http://github.com/keras-team/keras/issues/10058

* In Tensorflow backend, let batch norm call to FusedBatchNorm only NHWC format, also gamma and beta are not None.

Test result:
test env: with Tensorflow(commit a543d9471047ca3f6881c87105fcbe2cdff9207d Date:   Thu May 10 17:43:30 2018, local build), python3.4, centos7.4
test cases:
  "pytest  ./tests/keras/layers/normalization_test.py"  <all passed>
  "pytest  ./tests"      <keep same result as without this commit's modification on BN>

* fix code sytle.

* 1. Add axis parameter in backend's batch_normalization functions.
2. Refine the batch_normalization function in tensorflow backend, Let's it call to fused batch norm as much as possible.

Thanks the coments from fchollet.

* Trigger

* 1. add default value -1 for parameter axis in batch_normalization function in backend.
2. fix some code style.
Thanks the comments from fchollet.

* Handle capitalised extensions in list_pictures (#10220)

#10219

* Typo fix (#10293)

* Fix doc  (#10308)

* Fix naming convention

* Add missing doc

* Fix typo

* Improve docstrings of applications (#10310)

* Add pooling options in MobileNetV2 (#10313)

* Add pooling option

* Add pooling test

* Fix doc (#10327)

Fixed doc

* Handle `mask` in `TimeDistributed` wrapper. (#10242)

* equip TimeDistributed with mask and unspecified input length

* fix bugs in theano. add test on timedistributed + masking

* skip tests on cntk with multiple unspecified time lengths.

* move static shape inference to theano_backend, add docstring, etc.

* fix format

* Split `applications` and `preprocessing` modules. (#10339)

* Split `applications` and `preprocessing` modules.

* Fix dependencies.

* Move tests for applications (#10341)

* Improve the docstring of Conv3DTranspose (#10342)

* Add depth as third dimension in docstring of
  Conv3DTranspose in convolutional.py in keras.layers

* Reduce tests for applications (#10346)

* Reduce tests for applications

* Make selection over all models random

* Add an advanced activation layer for ReLU (#10322)

The max_value argument can not be used in a layer, except
custom layer or Lambda. Hence, similarly to LeakyReLU or
for example Softmax, this PR adds a layer for ReLU,
enabling also a capped ReLU to be used.

* FIX: Tensorboard callback only supports logging Embeddings layer weights (#7766)

* Embed layer-outputs rather than layer-weights in TensorBoard callback

* Update docstring and allow multiple inputs

* Fix tests

* Renaming

* Set learning phase

* Compute embeddings in batches

* Pass embedding data explicitly

* Actually process embeddings in batches

* Allow multiple inputs and validate input data

* Add example

* Delete utils.py

* Revert uncorrectly resolved merge-conflict

* Minor renaming

* Add comment clarifying the design choice

*  Fix HDF5Matrix issue when working in conjunction with TimeSeriesGenerator (#10334)

* Fix issue when working in conjunction with TimeSeriesGenerator

The TimeSeriesGenerator class uses xrange through six which caused an IndexError

* Add test

* Add corresponding test

* Fix for python3

* Simplified code

* Fix indent

* Fix test

* Supporting channels_first data format with crossentropy losses (#9715)

* Add error message when calling `summary` on unbuilt subclassed models.

* Prepare 2.2.0 release.

* Fix a version number (#10361)

* Update to Keras Applications 1.0.2 (fixes NASNet issue).

* Add tests for inputs set dynamically (#10367)

* CuDNN RNN layers nested in TimeDistributed are not converted when loading (#10357)

* Add a unit test for CuDNNGRU conversion with TimeDistributed.

* Extract duplicated function convert_model() to _convert_model_weights().

* #10356 Convert weights of CuDNN/plain RNN nested in TimeDistributed.

Same case as for Bidirectional, except that in TimeDistributed there's only
one nested layer instead of two.

* Style fix

* Update docs for 2.2.0.

* Add spatial dropout and 3D global pooling to docs (#10373)

* spatial dropout in docs

* 3d global pooling in docs

* Doc update (#10376)

A couple of variables are "used" in two examples without being defined. For consistency with other examples where auxiliary dimensions are defined, I think it would be better to explicitly assign them a value. I just used made up values, feel free to change to whatever makes more sense!

* Preserve input shape data when serializing deferred-build Sequential models.

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings

* Rebase to latest Keras April 20 2018 (#71)

* Improve tests by designating dtype of sample data (#9834)

* Document that "same" is inconsistent across backends with strides!=1 (#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* #9642 Add kwarg and documentation for dilation_rate to SeparableConvs (#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (#9866)

* Fix image_ocr.py example ValueError (#9869)

* Fixed the NASNet issue. (#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (#9920)

* Fix `batch_dot` of CNTK when `axes=None` (#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (#9922)

* Fix stateful metrics when passing dict to compile (#9894)

* Added note to manually install h5py where needed (#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with #8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (#9937)

* fix TimeSeriesGenerator glitch (#9899)

* Added an error message for undefined shape on NASNet. (#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (#9944)

* Chenta/cntk bn (#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - royw…
sandeep-krishnamurthy pushed a commit to awslabs/keras-apache-mxnet that referenced this pull request Aug 14, 2018
@roywei @sandeep-krishnamurthy
Rebase to latest Keras April 20 2018 (#71)
56134d3 
* Improve tests by designating dtype of sample data (keras-team#9834)

* Document that "same" is inconsistent across backends with strides!=1 (keras-team#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* keras-team#9642 Add kwarg and documentation for dilation_rate to SeparableConvs (keras-team#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (keras-team#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (keras-team#9866)

* Fix image_ocr.py example ValueError (keras-team#9869)

* Fixed the NASNet issue. (keras-team#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (keras-team#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (keras-team#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (keras-team#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (keras-team#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (keras-team#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (keras-team#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (keras-team#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (keras-team#9920)

* Fix `batch_dot` of CNTK when `axes=None` (keras-team#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (keras-team#9922)

* Fix stateful metrics when passing dict to compile (keras-team#9894)

* Added note to manually install h5py where needed (keras-team#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (keras-team#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with keras-team#8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (keras-team#9937)

* fix TimeSeriesGenerator glitch (keras-team#9899)

* Added an error message for undefined shape on NASNet. (keras-team#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (keras-team#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (keras-team#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)

* Chenta/cntk bn (keras-team#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (keras-team#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* add multi gpu model example (#85)

* add multi gpu model

* specify param name

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings
sandeep-krishnamurthy pushed a commit to awslabs/keras-apache-mxnet that referenced this pull request Aug 14, 2018
@roywei @sandeep-krishnamurthy
Keras MXNet 2.1.6 Release (#101)
84e6ff2 
* Improve tests by designating dtype of sample data (keras-team#9834)

* Document that "same" is inconsistent across backends with strides!=1 (keras-team#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* keras-team#9642 Add kwarg and documentation for dilation_rate to SeparableConvs (keras-team#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (keras-team#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (keras-team#9866)

* Fix image_ocr.py example ValueError (keras-team#9869)

* Fixed the NASNet issue. (keras-team#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (keras-team#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (keras-team#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (keras-team#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (keras-team#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (keras-team#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (keras-team#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (keras-team#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (keras-team#9920)

* Fix `batch_dot` of CNTK when `axes=None` (keras-team#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (keras-team#9922)

* Fix stateful metrics when passing dict to compile (keras-team#9894)

* Added note to manually install h5py where needed (keras-team#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (keras-team#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with keras-team#8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (keras-team#9937)

* fix TimeSeriesGenerator glitch (keras-team#9899)

* Added an error message for undefined shape on NASNet. (keras-team#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (keras-team#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (keras-team#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (keras-team#9944)

* Chenta/cntk bn (keras-team#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (keras-team#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* add multi gpu model example (#85)

* add multi gpu model

* specify param name

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings

* Update CNN benchmark result (#97)

* update benchmark numbers

* update number

* update result

* Update RNN benchmark results (#98)

* Fix pep failures

* Add 8 GPUs RNN benchmark results

* remove checking data format (#102)

* update imagenet result (#103)
sandeep-krishnamurthy added a commit to awslabs/keras-apache-mxnet that referenced this pull request Aug 14, 2018
@sandeep-krishnamurthy
Prepare for keras-mxnet 2.2 release (#117)
b6cfa49 
* Document that "same" is inconsistent across backends with strides!=1 (#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* Add h5py to dependencies

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Added note to manually install h5py where needed (#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Added an error message for undefined shape on NASNet. (#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Make conv_invalid_use and pooling_invalid_use efficient (#9944)

* Chenta/cntk bn (#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* fixing typos (#10016)

* Add `separable_conv2d` for Theano (#10003)

* Add `separable_conv2d` for Theano

* Enable the layer test for `separable_conv2d`

* Fix the strides for 1x1 conv

* Refactor topological part of `engine` module (#10023)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Fix Bidirectional Regularization (#10012)

* Fix Bidirectional Regularization

Override the Wrapper `get_updates_for` and `get_losses_for` methods so that contributions from both the forward and backward layers are included in Bidirectional.

* Use Parent for Calculating Inner Inputs

Remove unneeded inner input calculations.

* Simplify Bidirectional Losses

* Add Bidirectional Unit Tests

Test Bidirectional updates and losses.

* Remove Trailing Whitespace

* Fix Bidirectional Loss Inputs

* Add Tests for Conditional Updates/Losses

* Remove Whitespace

* Refactor training part of `engine` module. (#10029)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Fix `int_shape` of Theano and Refactor associated lines (#10030)

* Add exceptions for `batch_dot` (#10020)

* Enable Xception to work on Theano and CNTK (#10024)

* Enable Xception to work on Theano and CNTK

* Fix different predictions over all the backends

* Add support for passthrough arguments to NumpyArrayIterator (#10035)

* Add support for second output to NumpyArrayIterator

* Enable Model subclassing API (#10046)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Refactor Network to prepare support for Model subclassing

* Finish enabling Model subclassing.

* Add `long_description` field in setup.py.

* Remove unused import

* Increase pytest duration from 10 mins to 20 mins (#10072)

* [RELNOTES] Simplify implementation of Sequential and remove legacy Merge support (#10077)

* Refactor topological part of Keras engine.

* Fix imports

* Fix merge mixup.

* Refactor training part of the Keras engine.

* Fix unit tests.

* Refactor Network to prepare support for Model subclassing

* Finish enabling Model subclassing.

* Simplify Sequential implementation.

RELNOTES: This breaks weight loading and model loading/saving for models from Keras 0.* that used Merge layers. The Merge layer has been deprecated for 2 years.

* [RELNOTES] Remove support for Keras 0.* Merge layer and associated functionality, which was scheduled for 08/2017.

* fix typo (#10078)

* Add documentation to several activation functions (#10066)

* Add documentation to several activation functions

* Fix style issues.

* Small style fixes.

* [RELNOTES] Introduce `preprocessing.image.save_img` and remove deprecated imsave method in neural style transfer example (#9996)

* imsave method in scipy.misc package is deprecated - now using imageio

* updated save_img method to use array_to_img method.  also updated the neural style transfer example to use the new save_img method

* forgot to commit changes - updated save_img

* added file_format and **kwargs parameter to save_img and updated docstring

* removed space at the end of a line in save_img method.  updated instances of imsave in example scripts with save_img method.

* added kwargs to docstring.  removed additional whitespace lines

* removed trailing whitespace

* Extensive style fixes in `preprocessing.image`.

* [RELNOTES] Allow loading external backends (#10034)

* load external backend

* safety++

* Excpetion -> ValueError

* Revert TF version to 1.7 on Travis CI. (#10101)

* New Callback: EarlyBaselineStopping (#10061)

* Initial Commit

* Continued changes

* Alpha version

* Added support to make sure that previous epochs, which may pass the
baseline test, are kept in variable history.

* Code formatting

* Code formatting

* Code formatting to address CI errors

* Code formatting for CI errors

* Initial unit test code

* Adjust for epoch being zero-based

* Code formatting

* Unit tests added

* Code formatting

* Code formatting

* Factorized the unit test

* Code formatting

* Refactored to be part of EarlyStopping and modified unit tests

* Code formatting

* Adds MobiletNetV2 to applications (#10047)

* [RELNOTES] Allow symbolic tensors to be fed to models (with TF backend) (#10087)

* Allow symbolic tensors to be fed to models (with TF backend)

* Skip tensor feeding tests when TF>=1.8 not available.

* [RELNOTES] Fix EarlyStopping API

* Fix shape mismatch in `rnn()` of tensorflow_backend (#10038)

* Fix shape mismatch in `rnn()` of tensorflow_backend

Fix the shape mismatch in `rnn()` with `not unroll` and `mask is not None` of the Tensorflow backend.

Problem: If the rnn cell has any (recurrent) `states[i]` whose shape is different from that of the `output` (`states[0]`), there will raise an `ValueError` when updating that state.

Reason: This is because the `tiled_mask_t` is not updated correctly for each `states[i]` but instead is simply copied from that of the `output` (`states[0]`).

Solution: Tile the `mask_t` with the correct shape of each `states[i]`. Notice that in a similar situation with `unroll is True`, the `tiled_mask_t` is handled correctly.

* add unit_test for rnn() with states whose shape is different from that of the output.

* Revert "add unit_test for rnn() with states whose shape is different from that of the output."

This reverts commit f1df2a58ff635bbf698444e3d7403785a92dfed1.

* Simplify the unit_test for rnn with additional states

* [RELNOTES] Default `Flatten` layer’s `data_format` argument to `None`.

* #10080 Convert CuDNN weights in nested Model. (#10081)

* #10080 Convert CuDNN weights in nested Model.

- similar problem to nesting in Bidirectional (#8860)
- quick fix: just copy/paste. I'll refactor it later
- also convert biases from H5 Dataset to np.array for reshape() (#9662)

* Refactor keras.engine.saving.preprocess_weights_for_loading().

- less duplication
- extracted conversion methods for Bidirectional/Model/Sequential

* Format docstrings to follow the project code style.

* Move tests of CuDNN RNN weight conversion to a more proper place.

- move from cudnn_recurrent_test.py to test_model_saving.py
- adjust imports to be consistent

* Make better tests for CuDNN RNN weight conversion.

- add nested models (#10080)
- various model types: add Model, Sequential (not only Sequential)
- convert weights on model, not layer (not test nesting in models)
  - test just by save/load model weights instead of calling preprocess_weights_for_loading() directly

* Check GPU support via tf in pytest skipif with short-circuit evaluation.

It seems that multiple skipif decorators get evaluated eagerly, not lazily.
Thus it fails on theano and cntk backends.

I don't understand why the tests didn't fail until now.
Maybe some change in pytest?

* Refactor (deduplicate) skipif decorators for TensorFlow and GPU.

At least multiple occurrences within a test module.
Now we can't import from `tests/` and `keras.utils.test_utils` don't se pytest.
Otherwise we can define the marker only once at all.

* Fix PEP8 (whitespace).

* Add `separable_conv1d` (#10125)

* Add `separable_conv1d` for Theano

* Add `separable_conv1d` for CNTK

* Fix preprocess_input not working with int arrays (#10134)

* Make MobileNet tests random (#10132)

* Sample weighted ImageDataGenerator (#10092)

* Add support for sample_weight in ImageDataGenerator.flow

* Added test for sample weighted imagedatagen

* clarified docs + PEP8

* pep8 - blank line

* sample_weight argument after shuffle

* RNN docstring fixes; pass `maximum_iteration` argument to `while_loop` in TF.

* Use `embedding_lookup` for `gather` in TF backend (enables partitioned variables).

* Add `data_format` argument to Conv1D; docstring style fixes.

* Further fixes.

* Fix initializers (#9963)

* fix VarianceScaling

* Correct standard initializer testing

* Add test for truncated normal in backend

* Use correct theano function for truncated_normal

* Fix sloppiness in correction

* fix PEP

* improve style initialiser fix

* fix line length

* Use NCW/NWC for conv1d data format in TF backend.

* Model loading: do not return inside `try` block.

* Rely on `Flatten` layer to do data_format conversion in ResNet50, VGG16, VGG19.

* Remove potentially misleading warning messages in `applications`.

* Fix typo.

* Remove useless super delegation.

* Remove batch_size when doing stepwise fit (#10144)

`batch_size` is always `None` , because `steps_per_epoch` and `batch_size` are mutually exclusive.
Passing batch_size seems irrelevant as `None` is its default value in `test_loop`

* Add exceptions for `fit_loop` (#10145)

* Style fixes (#10148)

* Fix ConvLSTM2D unit_forget_bias initializer

* Avoid a warning by using  'x = x * y' instead of 'x *= y' (#10158)

* Fix undefined behaviour: preprocess_input copying/not copying the input arrays (#10153)

* Add copy option for image preprocessing

* Fix unnecessary import

* Fix style

* fix test error

* Make modifications in-place instead

* vae examples fixes (#10062)

* vae examples fixes

* white spaces around op

* comments and docstring fixes

* comments and docstring fixes

* comments and docstring fixes

* fixes on docs

* docs and spacing

* Merge 2 functions together in applications MobileNetV2 (#10163)

* merge 2 functions together

_inverted_res_block() and _first_inverted_res_block() are nearly the same. Merged them into one function
1. skip "Expand" part for 0 block
2. made layers names similar to original TF graph names

* added "mobl_" to prefix, pep8 fix

* remove dropout parameter

* concise prefix name

* Remove named argument from schedule function (#10178)

* Add missing doc (#10188)

* Best to set self.built=True at the end of build() (#10191)

When using Keras on TensorFlow (in graph mode), via `tf.keras`, then calling `self.add_weight()` fails if `self.built==True`, so it is best to encourage users to set `self.built=True` at the *end* of their `build()` method, rather than just "somewhere".

* Clean up preprocessing of `depthwise_kernel` for Theano (#10189)

* Allow dynamic backends in _need_convert_kernel (#10111)

* Fix _need_convert_kernel for external backends

* Don't assume external backend won't support NASNet

* Update from review comments

* fix TensorBoard callback with unit test (#10173)

* Allow project specific config files in Keras (#10183)

* Allow project specific config files in Keras

* Clearer code, updated comment

* Update cifar10_resnet.py (#10199)

change the comments on line 133.

* Adds height_shift_range to preprocessing.image doc and adds support for indentation in auto-generated doc (#10194)

* Update README.me

* Mobilenetv2 explanation  (#10174)

* i add mobilenetv2 to the table

* dd explanation for mobilenetv2

* add explanation for mibilenetv2

* Make multi_gpu_model serializable.

* Skip tests for multi gpu

* Fix slice namespace collision in backend.

* Skip multi_gpu tests for other backends than TF

* Replace np.ceil() with a faster operation (#10184)

* Replace ceil() with faster a operation

Replacing np.ceil() with faster operations, as suggested in #8488

* Revert "Replace ceil() with faster a operation"

This reverts commit 74fe60b445377b4f1be1d0a36b4777d7ed4f1c1b.

* Replace np.ceil() with a faster operation

* Fix syntax error

* Remove trailing whitespace

* Explicitly mention using a Sequence object in val (#10223)

* Grammatical error - "inputs channels" rather than "input". (#10217)

* Fix duplicated argname: num_gpus === parts (#10228)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix NASNet (#10209)

* Fix NASNet

* Update weight files

* In-place split to avoid inter-device duplication (#10230)

New Benchmark by in-place split:

>> keras.application.Resnet50 224x224x3 (NCWH; NVidia Tesla P100 x 4)
 input_shape = 3x224x224, batch_size =  96 x 4: 392(images/sec) => 417(images/sec)
 input_shape = 3x299x299, batch_size =  64 x 4: 229(images/sec) => 244(images/sec)
 input_shape = 3x224x224, batch_size =   8 x 4: 148(images/sec) => 163(images/sec)

>> keras.application.InceptionV3 (NCWH; NVidia Tesla P100 x 4)
 input_shape = 3x224x224, batch_size = 128 x 4: 488(images/sec) => 526(images/sec)
 input_shape = 3x299x299, batch_size =  96 x 4: 270(images/sec) => 294(images/sec)
 input_shape = 3x224x224, batch_size =   8 x 4: 146(images/sec) => 158(images/sec)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Increase test coverages by adding invalid CNTK usecases (#10236)

* Remove Sequential.model deprecation warning (#10256)

* Remove Sequential.model deprecation warning

* Remove dead line of code

* Increase test coverages by factorizing CNTK pads (#10259)

* Refactor ImageDataGenerator (#10130)

* Create get_random_transform and refactor

* Fix style and add tests

* Add more tests

* Fix documentation error

* Fix documentation style issue

* add apply_affine_transform

* document transformation dictionary

* Doc style fix

* Remove deprecated model.model from engine/saving (#10275)

* Typo in docstring for softplus (#10277)

Softplus docstring missing a parenthesis.

* Make Dot documentation inline with Concatenate (#10271)

Doc expects a list containing 2 tensors.

* Fixes automatic doc generation problem with nested lists. Adds a new test (#10212)

* Fixes automatic doc generation problem with indented lists. Adds a new test

* Some style fixes on doc automatic generation files

* Fixes a bad space in convolutional_recurrent.py

* Changes the test_doc_auto_generation in order to include a doc string taken from the codebase. Allows text lines following nested lists

* Use count_params function for non_trainable_count. (#10280)

* load_weights will fail if shape mismatch (#10266)

Fix for #10265

* Adds to and alphabetizes documentation of Layer base class. (#10282)

* Alphabetizes and adds to layers doc.

* Responding to @cais comments

* fix spacing.  Remove in(out)bound_nodes

* Non training Batch Norm operator has bad performance for it running into tensorflow's non fused batch norm API (#10207)

* When use tensorflow as backend, let batch norm run into fused batch norm as much as possible, which has better performance.

fix issue: http://github.com/keras-team/keras/issues/10058

* In Tensorflow backend, let batch norm call to FusedBatchNorm only NHWC format, also gamma and beta are not None.

Test result:
test env: with Tensorflow(commit a543d9471047ca3f6881c87105fcbe2cdff9207d Date:   Thu May 10 17:43:30 2018, local build), python3.4, centos7.4
test cases:
  "pytest  ./tests/keras/layers/normalization_test.py"  <all passed>
  "pytest  ./tests"      <keep same result as without this commit's modification on BN>

* fix code sytle.

* 1. Add axis parameter in backend's batch_normalization functions.
2. Refine the batch_normalization function in tensorflow backend, Let's it call to fused batch norm as much as possible.

Thanks the coments from fchollet.

* Trigger

* 1. add default value -1 for parameter axis in batch_normalization function in backend.
2. fix some code style.
Thanks the comments from fchollet.

* Handle capitalised extensions in list_pictures (#10220)

#10219

* Typo fix (#10293)

* Fix doc  (#10308)

* Fix naming convention

* Add missing doc

* Fix typo

* Improve docstrings of applications (#10310)

* Add pooling options in MobileNetV2 (#10313)

* Add pooling option

* Add pooling test

* Fix doc (#10327)

Fixed doc

* Handle `mask` in `TimeDistributed` wrapper. (#10242)

* equip TimeDistributed with mask and unspecified input length

* fix bugs in theano. add test on timedistributed + masking

* skip tests on cntk with multiple unspecified time lengths.

* move static shape inference to theano_backend, add docstring, etc.

* fix format

* Split `applications` and `preprocessing` modules. (#10339)

* Split `applications` and `preprocessing` modules.

* Fix dependencies.

* Move tests for applications (#10341)

* Improve the docstring of Conv3DTranspose (#10342)

* Add depth as third dimension in docstring of
  Conv3DTranspose in convolutional.py in keras.layers

* Reduce tests for applications (#10346)

* Reduce tests for applications

* Make selection over all models random

* Add an advanced activation layer for ReLU (#10322)

The max_value argument can not be used in a layer, except
custom layer or Lambda. Hence, similarly to LeakyReLU or
for example Softmax, this PR adds a layer for ReLU,
enabling also a capped ReLU to be used.

* FIX: Tensorboard callback only supports logging Embeddings layer weights (#7766)

* Embed layer-outputs rather than layer-weights in TensorBoard callback

* Update docstring and allow multiple inputs

* Fix tests

* Renaming

* Set learning phase

* Compute embeddings in batches

* Pass embedding data explicitly

* Actually process embeddings in batches

* Allow multiple inputs and validate input data

* Add example

* Delete utils.py

* Revert uncorrectly resolved merge-conflict

* Minor renaming

* Add comment clarifying the design choice

*  Fix HDF5Matrix issue when working in conjunction with TimeSeriesGenerator (#10334)

* Fix issue when working in conjunction with TimeSeriesGenerator

The TimeSeriesGenerator class uses xrange through six which caused an IndexError

* Add test

* Add corresponding test

* Fix for python3

* Simplified code

* Fix indent

* Fix test

* Supporting channels_first data format with crossentropy losses (#9715)

* Add error message when calling `summary` on unbuilt subclassed models.

* Prepare 2.2.0 release.

* Fix a version number (#10361)

* Update to Keras Applications 1.0.2 (fixes NASNet issue).

* Add tests for inputs set dynamically (#10367)

* CuDNN RNN layers nested in TimeDistributed are not converted when loading (#10357)

* Add a unit test for CuDNNGRU conversion with TimeDistributed.

* Extract duplicated function convert_model() to _convert_model_weights().

* #10356 Convert weights of CuDNN/plain RNN nested in TimeDistributed.

Same case as for Bidirectional, except that in TimeDistributed there's only
one nested layer instead of two.

* Style fix

* Update docs for 2.2.0.

* Add spatial dropout and 3D global pooling to docs (#10373)

* spatial dropout in docs

* 3d global pooling in docs

* Doc update (#10376)

A couple of variables are "used" in two examples without being defined. For consistency with other examples where auxiliary dimensions are defined, I think it would be better to explicitly assign them a value. I just used made up values, feel free to change to whatever makes more sense!

* Preserve input shape data when serializing deferred-build Sequential models.

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - roywei@

* Fix bug - mxnet backend should not override keras config data_format to channels_first. Only warn of low performance

* Conv3d() operator implementation for Keras2.0 using MXNet backend (#40)

* conv3d implementation for keras2.0 as MXNet backend

* conv3d implementation/testing for keras2.0 using MXNet backend

* keeping -n option in pytest.ini file

* fixed comments given by Sandeep

* Add Conv1D support for MXNet backend (#44)

* Add Conv1D support for MXNet backend

* Fix CR comments

* Conv2d transpose (#47)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* enable test case in topology

* Enable performance optimization for conv operators with MXNet backend. Make MXNet default backend with this branch (#48)

* Fix conv kernel shape bug for TF backend. (#50)

* Add support for keras multi_gpu_model() API with MXNet backend (#49)

* Add support for keras multi_gpu_model() API with MXNet backend. Autoset GPU0 context on GPU machine

* Fix typo

* Add SAME padding mode support for pooling operator. (#51)

* Add rnn() operator for MXNet backend with unrolling and masking feature (#46)

* Adding rnn() operator in Keras2.0 with MXNet as backend with unroll=True and Masking=True/False and enabled relevant testcases. Also, modified couple of operators.

* Modified comments

* Added comments to a method

* Enable categorical crossentropy testcases and made minor changes

* Modified message

* nit

* Added detail description of handling variable length input in RNN

* Skip conv2d_transpose and conv3d_transpose test-case for MXNet backend and minor changes in rnn()

* Adamax and NAdam optimizer for MXNet backend (#54)

* Add Adamax optimizer for MXNet backend

* Fix lr and adamax params

* Add Nadam optimizer for mxnet backend

* Add Conv3d transpose (#52)

* conv3d tranpose, enabled test case

* update kernel shape

* replace conv2d_transpse conv3d_transpose with convnd_transpose

* update value errors with MXNet Backend info, fix typo

* add check for conv3d transpose only supports gpu with cudnn

* update context check

* diable conv3d transpose test

* fix typo in comment

* Rebase to latest Keras - April 3, 2018

* Add build badges

* Fix multi_gpu API bug for CPU. Fix PEP. (#64)

* Fix multi_gpu API bug for CPU. Fix PEP.

* fix embedding layer bug (#61)

* fix embedding bug

* addressed comments, enabled more test cases

* add keras test

* reduce line length

* fix style, add blank lines

* Benchmark (#55)

* add conv2d_transpose

* conv2d transpose for both channels, enabled test case

* add detailed comments and examples, fix style issue

* add benchmark scripts for resnet and imagenet data

* combine scripts

* fix args

* fix num of gpus

* update log

* multi_gpu_model only support tf

* add benchamrk scripts for synthetic data

* update read me and scripts

* add mxnet traing result table

* update on readme

* add cifar10 dataset and enable various resnet layers

* fix compile for mxnet multiple gpu

* update callbacks

* update synthetic data script, add credits

* undo new line

* update readme, addressed pr comments

* update readme

* benchmark scripts style fix (#66)

* style fix

* remove unused import, fix line too long

* adrressed pr comments

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend (#65)

* Added keras util API for conversion of data tensor from channels_last to channels_first using MXNet backend

* Modified comments

* Addressed review comments and made the API more generic accross backends

* Removed shape check

* Modified comments

* Added edge cases

* moved helper method as nested

* Added RNN benchmark scripts (#69)

* Added RNN benchmark scripts

* Fixed new line in bash script

* Removed different backend code and modified comments

* Removed spacing

* Automated the wikiText2 download script

* Added dataset_util functionality to have more flexible code

* Added minor comments

* modified minor comments

* Fixed the multi-gpu context (#68)

* Update benchmark result (#70)

* update benchmark result

* update result

* simplify folder structure

* add image result

* add note

* add note

* rebase to latest Keras - April 20, 2018, fix bug and unit tests

* Added detailed RNN results (#73)

* Added detailed RNN results

* Modified table content and added CUDA version

* fix keras examples (#72)

* fix auto encoder examples

* update other examples

* fix style and add ctc not implemented error

* Added Detailed RNN results (#77)

* Modified RNN benchmark document

* Added minor comments

* fixed broken image link

* Added API to extract metrics from a test and also added epoch parameter (#78)

* Add mxnet backend tutorial documents (#76)

* add performance tips document

* update warning

* add docs from wiki

* add initial multi gpu doc, simplified installation doc, fix benchmark doc typo

* update install steps

* add multi_gpu_model tutorial

* Support exporting model as MXNet model (sym, params). (#80)

* Support exporting model as MXNet model (sym, params).

* Return data_names and data_shapes

* add unit tests for mxnet model save API

* Add test with LSTM layer for mxnet model save API

* Add support for functional Model graphs in save_mxnet_model API

* Add additional logging for cnn benchmarks (#89)

* add extra logging

* add logging for cnn synthetic

* fix log name

* fix file name

* Log RNN benchmark results (#90)

* Make benchmark result logging available in RNN scripts

* Make log file name consistent across CNN and RNN benchmarks

* fix pytest errors (#93)

* Cherry pick keras-team/keras 2.1.6 missing 3 commits into awslabs/keras-apache-mxnet (#96)

* update multi_gpu api in benchmark scripts (#95)

* update multi_gpu

* update logging

* fix logging

* fix logging

* fix speed format

* remove learning rate log

* Revamp keras-mxnet docs (#82)

* Update main README and move mxnet_backend_docs under docs

* revisit installation mxnet backend docs

* revisit multi_gpu_training mxnet backend docs

* revisit performance_guide mxnet backend docs

* revisit using rnn with mxnet backend in mxnet backend docs

* add save_mxnet_model tutorials in mxnet backend docs

* Fixing review comments from aaron

* Resolve CR comments on save_mxnet_model tutorial

* Fix broken links, update tutorial links in the mxnet_backend code

* revamp benchmark results readme

* Benchmark results README page revamp

* Add library versions

* Remove too detailed benchmark results. Summarize in README

* Get back detailed results document

* Remove experiemental RNN benchmarks from README

* addressed review comments on benchmark results

* Set latest stable dependency of h5py to avoid warnings

* Rebase to latest Keras April 20 2018 (#71)

* Improve tests by designating dtype of sample data (#9834)

* Document that "same" is inconsistent across backends with strides!=1 (#9629)

* Document that `"same"` is inconsistent across backends with `strides` != 1

* Use "[here](...)"

* #9642 Add kwarg and documentation for dilation_rate to SeparableConvs (#9844)

* Add kwarg and documentation for dilation_rate to SeparableConvs

* Fix pep8 complaint

I forgot to check the style before committing. Pep8 was complaining about a missing whitespace after comma, now it's fixed.

* fit/evaluate_generator supporting native tensors (#9816)

Currently, `fit/evaluate_generator` don't support this case without this fix.
But framework-native data tensors are already supported by `_fit_loop` and `_test_loop`.

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Add h5py to dependencies

* Fixed typo. (#9866)

* Fix image_ocr.py example ValueError (#9869)

* Fixed the NASNet issue. (#9865)

* Fixed the NASNet issue.

* Nasnet doesn't require flatten.

* Updated documentation accordingly.

* Removed generate dropout ones from recurrent. (#9892)

* Removed generate dropout ones from recurrent.

* Fixed index issue.

* Fix `in_test_phase` of CNTK and Add its tests (#9902)

* Fix dtype designation for `variable` of CNTK and Add its tests (#9903)

* import `pydot`, improve error messages about `pydot` and GraphViz, bump to `pydot >= 1.2.4` (#9904)

* REL: bump to `pydot >= 1.2.4` in `extras_require`

* MAI: import pydot (as required in `extras_require`)

* MAI: refine error messages for `pydot` and GraphViz

distinguish between absence of `pydot` and failure to find
the executables of GraphViz in the $PATH.

* DEV: ignore `.pytest_cache`

* Fix documentation of flow_from_directory() (#9910)

The way the documentation is parsed for the Keras website made some lines of the documentation beginning with "Default:" look funny. Also changed the documentation of return value to be clear that it always returns a batch of images.

* ModelCheckpoint: print previous best (#9911)

* multi_gpu_model supporting legacy/fullCPU/fullGPU (#9638)

Signed-off-by: CUI Wei <ghostplant@qq.com>

* Fix `batch_dot` of Theano when `axes=0` (#9920)

* Fix `batch_dot` of CNTK when `axes=None` (#9921)

* Fix `batch_dot` of TensorFlow when `axes=None` (#9922)

* Fix stateful metrics when passing dict to compile (#9894)

* Added note to manually install h5py where needed (#9830)

* Added notes to manually install h5py if needed

* Added FAQ entry on h5py

* deleted redundant remark about h5py

* updated FAQ to reflect dependency change

* fixed comment format to pass failing test

* removed new trailing whitespaces

* improved docstring format

* reverted callbacks.py

* fixed links in model.py

* updated faq.py

* link pointing to FAQ

* Add support for `constants` in Bidirectional wrapper (#9260)

* Add support fot `constants` in Bidirectional wrapper

* Add more tests for Bidirectional wrapper

* Fix `compute_mask` for Birectional with return_state=True

Fix `compute_mask` to properly support `return_state` introduced in Birectional with #8977

* Add test for Bidirectional with unknown timestamps

* Skip test for CNTK for unknown timestamps with Bidirectional

* avoid override the input constant when need broadcast sequential axis on rnn's constant

* Move _standardize_args to recurrent, remove duplication

* Fix  for Birectional when multiple masks are passed

* Updated for TF 1.7 (#9937)

* fix TimeSeriesGenerator glitch (#9899)

* Added an error message for undefined shape on NASNet. (#9891)

* Added an error message for undefined shape on NASNet.

* Forgot that the message should be present only when loading imagenet weights.

* Changed the message.

* Fix PEP8

* Allow shift_range to be 1-D array-like or int (#8869)

* Allow shift_range to be 1-D array-like or int

* Add docstrings

* Fix conflict resolution merge minor disaster

* remove stray line from merge

* Remove extra "tabs"

* Exclude multi-gpu utils when reporting coverages (#9942)

* Make conv_invalid_use and pooling_invalid_use efficient (#9944)

* Chenta/cntk bn (#9952)

* fix cntk static learning phase issue; add a test

* fix code style;add more comments

* add boolean support

* fix code style issue

* Immigrate reference operations to a separate module (#9948)

* Add MXNet Backend (#59)

* Adding MXNet backend template. Adding all basic Variable and Tensor operations (#1)

* add activation functions

* add activation functions

* fix some legacy

* fix some legacy

* cross entropy

* cross entropy

* fix name scoping introduced in 2.0

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* remove the logic for hacking RNN

* add pooling with utils

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* mxnet_backend graph fix, layer support  (#3)

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* Add dropout, l2_normalization, random_normal/uniform/binomial (#2)

* remove the logic for hacking RNN

* add pooling with utils

* add activation functions

* fix some legacy

* cross entropy

* fix name scoping introduced in 2.0

* remove the logic for hacking RNN

* add pooling with utils

* minor

* lint and name scope fix

* fix access protected var

* fix add neighbor, removed __eq__ in KerasSymbol

* fix eval function, unittest for placeholder and variable

* add unittests

* fix bug

* fix bug

* fix

* add some temporary fixes in mxnet backend. undo change to the pytest.ini

* Keras function not working is a known issue, add skip in the test

* fix random_uniform/constant

* fix legacy randomize methods

* Fix MXNet backend operator bugs. Enabled Keras backend tests

* add bias

* Add Amazon copyrights to License (#6)

* fix

* fix

* fix backend for mlp

* fix context management, add optimizers

* minor change

* undo changes on example

* fix eval

* minor cleanup

* fix some property usage

* fixing AlphaDroupout, not finished yet

* add mx model instantiate

* modifies training model construct logic, fix some tests. fix reshape layer.

* minor fix

* fix bias_add

* more fix on Dense and bias_add

* In progress commit

* fix comment

* small fix

* remove pytest.skip in conv3d. But it failed with theano backend in my workspace though.

* Add conv2d and in_topk operator for mxnet backend (#11)

* Skip BatchDot tests for Theano backend. (#12)

* BatchDot, Basic Batchnorm, Fix BiasAdd, Fix Conv2D, CodeCleanup (#14)

* Fix Conv2d shape issues and enable Conv2D UTs

* Remove redundant mxnet only unit tests

* Adding batch_dot, remove deconv, code comments and cleanup

* Remove buggy conv1d implementation

* Fix CR comments. Fix lint check issues

* Move mxnet specific code from keras engine to mxnet_backend. (#15)

* Move MXNet optimizers from keras optimizers to mxnet backend (#16)

* Fix bug in reshape. Minor rename to avoid local conflicts

* Bug fixes and enable/skip all Keras tests for mxnet backend (#21)

* test results - 374 passed, 235 skipped in 114.44 seconds

* fix/skip keras tests - tests/integration_tests, tests/keras/applications

* fix/skip keras tests - tests/keras/engine/test_topology

* fix/skip keras tests - tests/keras/engine/test_training

* fix/skip keras tests - tests/keras/legacy/

* fix/skip keras tests - tests/keras/preprocessing

* fix/skip keras tests - tests/keras/utils/

* Fix CR comments

* Fix issues in zero_padding. Fix/Enable tests/layers/convolutional_test

* Add momentum to batchnorm. Enable/skip tests in layers/core, local, merge, noise, normalization

* Skip RNN tests in keras/tests/layers/recurrent_test, wrappers_test

* Fix bug in spatial padding, enable/skip tests in loss,optimizers,callback,loss_weighting, model_saving

* Fix mxnet backend multi-gpu training (#31)

Fixing bug for mxnet backend to use multiple gpus.

* Fix performance issue - Batchnormalization, Conv operator (#35)

* Fix default axis for batchnorm layer for channels_first data_format

* Performance improvement by avoiding kernel transpose in conv operation for channels_first format

* Fix model - architecture, weights and both, load and save. (#36)

* Prepare initial version of mxnet related documentation in keras (#38)

* Skip failing unit tests for unsupported functionality in mxnet backend

* Fix pep tests reported by CI

* Use pytest module skip, revert kernel_shape logic

* remove data_format param from bias_add API

* Allow Predict() without compile for mxnet backend and enable tests.

contributor - royw…
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@lucasdavid @fchollet