Change batch_size descriptions to proper ones
#13422
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Since there're no gradients updated during `evaulate` and `predict` processes, changed their `batch_size` docstrings from `"Number of samples per gradient update"` to `"Number of samples per evaluation step"` and `"Number of samples to be predicted at once"`. (The sentence in fit remains unchanged.) I hope this fix would change related auto-generated documents as well.
Corrected `callbacks` description docstrings in `evaluate_generator` and `predict_generator`: "List of callbacks to apply during training" -> "- during evaluation", "- during prediction".
EthanJYK
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Oct 11, 2019
[For Reviewers Proficient in Korean] - framework-native tensors / TensorFlow data tensors: 이미 각 백엔드를 통해 텐서로 정의되어 있는 데이터들을 의미합니다. 이 경우 Keras는 placeholder를 생성하지 않고 곧바로 Tensor를 읽어들입니다. `프레임워크(예: TensorFlow)를 통해 이미 정의된 텐서`로 번역하였습니다. - `fit`의 validation_steps: 원문에 두 가지 경우가 별도로 서술되어 있습니다. 이 둘을 하나의 항목으로 합치되, 안에서 두 개의 경우로 분리하였습니다. - `fit`의 y: x의 경우 설명이 항목별로 나뉘어 구성된 반면 y의 경우 전체가 한 문단으로 작성되어 있습니다. 내용상 큰 차이가 없기 때문에 x와 같은 형식으로 통일하여 항목별로 작성합니다. - batch_size 항목들: 흐름이 자연스럽도록 문장의 순서를 살짝 조정합니다. - sample_weight, class_weight, sample_weight_mode 항목들: 설명을 보다 자세하게 덧붙여서 문장을 재구성했습니다. - 그 밖에 원문에 존재하는 오류는 PR을 통해 원문 수정 요청하면서 본문에도 정정하였습니다. 자세한 사항은 keras-team/keras#13422 참고바랍니다.
fchollet
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Oct 11, 2019
Kokomodo
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Jan 26, 2020
* First pass. * 2nd pass. * 3rd pass * 4th pass * Revert backend rnn. * 5th pass * Quick fixes * Simplification * Update Travis config to test on TF 2 * Fix some syntax error * Fix travis issues again * Fixes * Unit test fixes * Small fix. * Tf 2: fix optimizer weights naming collision issue (keras-team#12466) * rem get_session() call from multi gpu utils * tiny fix * optimizer fixes * fix tempfile * rem os.remove * rem tmpdir * ws fix * Fix docstring of util function. * Fix docstring style * TF-2: Remove get_session() call in multi_gpu_utils.py (keras-team#12465) * rem get_session() call from multi gpu utils * tiny fix * Fix in_top_k * Simplify bidirectional test * Move TensorBoard callback to v2 -- still need to fix some tests. * Small fixes. * Fix v1 tests. * Fix PEP8. * Fix initializers and update ops. * Disable test for TF print * Fix gradient test failure. * Fix test_model_with_external_loss * Small backend simplification * Fix convrnn tests. * Fix identity init * Remove irrelevant tests. * Fix conv2d_transpose * Fix PEP8 * Disable multiprocessing tests. * Fix tests. * Fix conv_rnn bug with cntk/theano * Fix TF1 test * Adding Loss, LossFunctionWrapper, MeanSquaredError classes. (keras-team#12859) * Adding Loss, LossFunctionWrapper, MeanSquaredError classes. * Fixing formatting issues. * Adding arguments list to MeanSquaredError. * Fix abstract method * Adding MeanAbsoluteError, MeanAbsolutePercentageError, MeanSquaredLogarithmicError and BinaryCrossentropy loss classes. (keras-team#12894) * Adding MeanAbsoluteError loss * Adding Binary Crossentropy loss. * Adding MeanAbsolutePercentageError loss. * Adding MeanSquaredLogarithmicError loss. * Adding #Arguments for some classes. * remove print statements * Update image preprocessing. * Update applications. * Remove ResNeXt networks (bug) and add tests. * Adding CategoricalCrossentropy and SparseCategoricalCrossentropy Loss classes (keras-team#12903) * Add categorical crossentropy loss. * Add sparse categorical crossentropy loss. * Adding support for `Loss` instances in model compile. (keras-team#12915) * Updating training utils. * training changes for supporting Loss instances. * Add weight broadcasting. * Saving test * Add correctness test. * Fix a number of tests. * Remove outdated test * Fix PEP8 * Change defaults of GRU and LSTM layers. * Rename lr to learning_rate in optimizers * Add missing loss classes * Fix tests. * Removing @symbolic from few tf backend ops. * Creating helper function for broadcast weights. * Adding Metric class. * Adding Metric class. * Adding sample weight unit test. * Adding Mean metric class and unit tests. * Addressed comments. * Adding control dependency op. * Adding no-op control dependencies to Theano and CNTK backends. * Fixing tests for TF1. * Fix doc string. * Fix backend issues. * Adding MeanMetricWrapper class. * Adding MeanSquaredError metric. * Framework changes for metrics part 1 * Metrics framework changes part 2 * Adding metrics correctness test. * Fix integration tests * Remove references to ResNeXt from docs. * Prepare 2.2.5 release. * Fix sklearn wrapper unit test in Python 3? * Fix sklearn regressor test? * Some Theano fixes. * Make metrics compatible with Theano * Theano fixes * Fix * Fixes * Recompute steps_per_epoch after each epoch in traingin_generator (keras-team#13037) * pep8 config in setup.cfg (keras-team#13196) * Theano fixes * Update optimizers for TF2. (keras-team#13246) 1. remove epsilon and decay for all optimizers 2. add iterations into weight list into RMSProp, Adagrad, Adadelta, Nadam * Fix results tracking for metrics in multi-output case * sync changes to _TfDeviceCaptureOp (keras-team#13255) * sync changes to _TfDeviceCaptureOp * adjust for wider compatibility * Documentation for `array_to_img`, `img_to_array` and `save_img` under `preprocessing.image` keras-team#12711 (keras-team#13252) * Add docstring of `save_img()` in `keras/preprocessing/image.py` Signed-off-by: Karel Ha <mathemage@gmail.com> * Add docstring of `img_to_array()` in `keras/preprocessing/image.py` Signed-off-by: Karel Ha <mathemage@gmail.com> * Add docstring of `array_to_img()` in `keras/preprocessing/image.py` Signed-off-by: Karel Ha <mathemage@gmail.com> * Add metric API changes (keras-team#13256) * Add metric API changes part 1 * Add metric API changes part 2 * Update metric __call__ calls to update state and result calls * Changing metric call for output loss metric to update_state and result calls. * Fix metrics support in Theano * Fix PEP8 * Introduces fixes for tensor equality in TF 2.0 * Minor fixes * Improve exception testing in test_training * Improve test syntax * Remove outdated tests * Only run label smoothing logic when necessary * Fix PEP8 * Update CI to run on TF 1.14 for TF1 * Disable a backend test for CNTK * Fix docs test * CNTK fixes * Disable test that hangs Travis * Disabled flaky cntk test * Reduce test flakiness * Disable CNTK SGD test * Disable test causing Travis to hang * Disable flaky CNTK test * Disable test that hangs Travis * Disable a couple more multiprocessing tests * Add ability for Layer to track sublayer attributes * Add support for layer attribute tracking (loss, updates, metrics) in layer subclasses, and standalone weight tracking * Fix theano backend * Fix PEP8 * Adding accuracy metric classes. (keras-team#13265) * Adding Accuracy metric class. * Adding BinaryAccuracy metric class. * Adding CategoricalAccuracy metric class. * Adding SparseCategoricalAccuracy metric class. * Adding TopK Accuracy metric classes. * Fixed review comments * Add metrics Hinge, SquaredHinge, CategoricalHinge * Add label conversion to hinge losses * Adding LogCosh, Poisson, KLDivergence, crossentropy metrics. (keras-team#13271) * Adding LogCosh, Poisson, KLDivergence metrics. * Adding crossentropy metrics. * Add metrics CosineSimilarity, MeanAbsoluteError, MeanAbsolutePercentageError, MeanSquaredError, MeanSquaredLogarithmicError, RootMeanSquaredError. * Reverse sign of cosine_similarity metric * Adding TruePositives, TrueNegatives, FalsePositives, FalseNegatives metric classes. (keras-team#13280) * Adding FalsePositive metric class. * Adding TruePositives, TrueNegatives, FalseNegatives metric classes. * Adding AUC, SensitivityAtSpecificity metrics. (keras-team#13289) * Adding AUC, SensitivityAtSpecificity metrics. * Fixed failing test. * Add SpecificityAtSensitivity metric. (keras-team#13294) * Add SpecificityAtSensitivity metric. * Fixing some lint issues. * Fixing some lint issues. * Adding Precision, Recall, Mean IoU part 1. * Adding Precision, Recall, Mean IoU part 1. * Add MeanIoU metric. * Add MeanIoU metric. * Fix metrics reporting / accumulation with fit_generator and evaluate_generator. * Remove deprecated example script * Remove deprecated example, fix conv filter example * Update examples * Fix some bugs * Update examples * Addressed PR comments. * Fix Theano tests. * Disable top_k metrics for TF1 * Reenable Precision and Recall with TF1 * Fix Py2 tests * Skip metric tests for CNTK * Fix py2 test * Fix py2 test * Update coverage threshold * Add back CPU to multi_gpu_utils available devices * Using K.is_tensor and K.is_variable (keras-team#13307) is_tensor_or_variable(x) is undefined and replaced by K.is_tensor(x) or K.is_variable(x). Fixes keras-team#13306. * Update lstm_seq2seq.py(from 22% to 87% acc) (keras-team#13269) * keras-team#13266 Update lstm_seq2seq.py(from 22% to 87% acc) I added the codes for applying one-hot encoding on the end of sentences about encoder_input_data, decoder_input_data, and decoder_target_data. I added an accuracy metric for model training. The original code has 22% accuracy, but the proposed code had 87% validation accuracy. * Update lstm_seq2seq.py I update code according to PEP8. * Update lstm_seq2seq.py Remove whitespace according to PEP 8. * Update babi_rnn.py (keras-team#13263) Change line 82 so the reg exp works as it says on token above in the comment because else it gives - AttributeError: 'NoneType' object has no attribute 'strip' * typo fixed (keras-team#13230) * Correct the DepthwiseConv2d docstrings - output shape (keras-team#13225) * fix in "Layer.compute_output_shape" description (keras-team#13210) * Added batch_normalization in the numpy backend. (keras-team#11556) * Finished the functions. * Started doing the test function. * Added the batch_normalization operation to the numpy backend. * forgot an argument * Complete the docs by adding data to multi-input/output example (keras-team#12775) * Complete the docs by adding data to multi-input/output example * Add seed for reproducibility * Fix Travis SSL issue. * keras-team#13239 Improved documentation for EarlyStopping/ReduceLROnPlateau, take validation_freq into account. (keras-team#13240) * Added messages about the future of multi-backend Keras. (keras-team#13315) * Added comments about the future of Keras. * Changed msg. * Fix sequence timeout deadlock (keras-team#13322) * Add a test for deadlock after sequence worker timeout * Call task_done even if the task timeouted * catch dead worker warning * fix line length * Increase deadlock detection timeout to prevent flakiness * Fix deprecation warnings related to TF v1 * Update README * Add a link to the metrics document (keras-team#13334) Link to the metrics document(/metrics) was missing in 'Compilation' section. Added one just as other explained arguments. * Fix thread safety issue * Correct spelling mistake (keras-team#13339) * fix keras-team#13341 math_ops to K (keras-team#13342) * Fix encoding error (keras-team#13355) * Add utf-8 encoding * Fix PEP8 error * Fix PEP8 error * Fix issue where the disable_tracking decorator obfuscates layer constructors. * Fix yaml version compat issue * Update local.py docstrings (keras-team#13373) * Update local.py stride value implies the input argument of 'stride', and dilation_rate implies the input argument of 'dilation rate' of Conv1D function. It is more explicit to express as code rather than using words stride value, dilation value. Or, at least both stride and dilation_rate should be written in code, not only dilation rate as before document * Update local.py mark as code snippet * Allowed to return the image as a Jupyter Image only if the extension is not pdf (keras-team#13383). (keras-team#13384) keras/utils/vis_utils.py * Fix file leak in CSVLogger (keras-team#13378) * Fix file leak in CSVLogger * Update callbacks.py * fix: `recurrent_activation` parameter's docstring (keras-team#13401) * typo_fix (keras-team#13395) * Prepare 2.3.1 release * Added the default activation of convolutional LSTM in the docs. (keras-team#13409) * Small refactors on the keras.utils module (keras-team#13388) * Use .format calls for string interpolation on utils * Use generators over listcomps whenever possible to save memory * Bumped tf2 version to 2.0.0 (keras-team#13412) * Change `batch_size` descriptions to proper ones (keras-team#13422) * Change `batch_size` descriptions to proper ones Since there're no gradients updated during `evaulate` and `predict` processes, changed their `batch_size` docstrings from `"Number of samples per gradient update"` to `"Number of samples per evaluation step"` and `"Number of samples to be predicted at once"`. (The sentence in fit remains unchanged.) I hope this fix would change related auto-generated documents as well. * Correct `callbacks` description docstrings Corrected `callbacks` description docstrings in `evaluate_generator` and `predict_generator`: "List of callbacks to apply during training" -> "- during evaluation", "- during prediction". * Update autogen.py (keras-team#13426) fix duplicate module name for callbacks module * Update io_utils.py (keras-team#13429) I just fixed Numpy -> NumPy in HDF5Matrix class. * Update pooling.py (keras-team#13467) * Update pooling.py Added Integer at the `pool_size` of `MaxPooling3D` * Update pooling.py Add Integer in `strides` and `pool_size` of 3D layers Added "If None, it will default to `pool_size`." to be consistent with explanation of 1D, 2D layer * Update pooling.py `channels_first` ->`"channels_first"` `channels_last` ->`"channels_last"` "channels_last"->`"channels_last"` * Update core.py (keras-team#13472) `channels_first` -> `'channels_first'` `channels_last`, "channels_last" -> `'channels_last'` data_format='channels_first' -> `data_format='channels_first'` data_format='channels_last' -> `data_format='channels_last'` * Fix h5py group naming while model saving (keras-team#13477) * Update np_utils.py (keras-team#13481) * Fix too many values to unpack error (keras-team#13511) * fix too many values to unpack error In the example script lstm_seq2seq_restore.py and lstm_seq2seq.py, when parse the data using line.split("\t"), it will return 3 values rather than 2, a simple modification can fix it. * add blankspace around operator Co-authored-by: François Chollet <francois.chollet@gmail.com> Co-authored-by: Fariz Rahman <farizrahman4u@gmail.com> Co-authored-by: Pavithra Vijay <psv@google.com> Co-authored-by: Victor Kovryzhkin <vik.kovrizhkin@gmail.com> Co-authored-by: Philip May <eniak.info@gmail.com> Co-authored-by: tanzhenyu <tanzheny@google.com> Co-authored-by: Taylor Robie <taylorrobie@google.com> Co-authored-by: Karel Ha <mathemage@gmail.com> Co-authored-by: Sebastian Höffner <info@sebastian-hoeffner.de> Co-authored-by: tykimos <adam.tykim@gmail.com> Co-authored-by: Kostas <kvogiat@gmail.com> Co-authored-by: Arnout Devos <arnoutdev@gmail.com> Co-authored-by: Keunwoo Choi <gnuchoi+github@gmail.com> Co-authored-by: Alexander Ivanov <avi2011class@yandex.ru> Co-authored-by: Gabriel de Marmiesse <gabrieldemarmiesse@gmail.com> Co-authored-by: Bharat Raghunathan <bharatraghunthan9767@gmail.com> Co-authored-by: Hendrik Schreiber <hs@tagtraum.com> Co-authored-by: Andrey Zakharevich <andreyzakharevich@gmail.com> Co-authored-by: Shiv Dhar <shivdhar@gmail.com> Co-authored-by: djstrong <djstrong@gmail.com> Co-authored-by: fuzzythecat <fuzzy0427@gmail.com> Co-authored-by: Naruu <esara2021@gmail.com> Co-authored-by: ftesser <fabio.tesser@gmail.com> Co-authored-by: Gregory Morse <gregory.morse@live.com> Co-authored-by: Andrew Naguib <andrew@fci.helwan.edu.eg> Co-authored-by: Haifeng Jin <jhfjhfj1@gmail.com> Co-authored-by: Michelle Vivita <mvivita88@gmail.com> Co-authored-by: Elton Viana <eltonvs@outlook.com> Co-authored-by: Junyoung Kim <Junyoung.JK.Kim@gmail.com> Co-authored-by: Denny-Hwang <48212469+Denny-Hwang@users.noreply.github.com> Co-authored-by: Thibault Buhet <38053590+Tbuhet@users.noreply.github.com> Co-authored-by: xemcerk <lisislzx@sina.com>
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Summary
Since there're no gradients to be updated during
evaulateandpredictprocesses, changed theirbatch_sizedocstrings from"Number of samples per gradient update"to"Number of samples per evaluation step"and"Number of samples to be predicted at once". (The sentence in fit remains unchanged.)Corrected
callbacksdescription docstrings inevaluate_generatorandpredict_generator:"List of callbacks to apply during training"->"- during evaluation","- during prediction".I hope this fix would change related auto-generated documents as well.
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