pypi keras 2.10.0
Keras Release 2.10.0
on Python PyPI

latest releases: 3.3.3, 3.3.2, 3.3.1...
20 months ago

Please see the release history at https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0 for more details.

What's Changed

  • Cleanup legacy Keras files by @qlzh727 in #14256
  • Sync OSS keras to head. by @qlzh727 in #14300
  • Update build script for GPU build. by @copybara-service in #14336
  • Move the LossReduction class from tf to Keras. by @copybara-service in #14362
  • Update keras API generate script. by @copybara-service in #14418
  • Adding extra target that are needed by PIP package dependency. by @copybara-service in #14421
  • Add test related targets to PIP package list. by @copybara-service in #14427
  • Sync OSS keras to head. by @copybara-service in #14428
  • Update visibility setting for keras/tests to enable PIP package testing. by @copybara-service in #14429
  • Remove items from PIP_EXCLUDED_FILES which is needed with testing PIP. by @copybara-service in #14431
  • Split bins into num_bins and bin_boundaries arguments for discretization by @copybara-service in #14507
  • Update pbtxt to use _PRFER_OSS_KERAS=1. by @copybara-service in #14519
  • Sync OSS keras to head. by @copybara-service in #14572
  • Sync OSS keras to head. by @copybara-service in #14614
  • Cleanup the bazelrc and remove unrelated items to keras. by @copybara-service in #14616
  • Sync OSS keras to head. by @copybara-service in #14624
  • Remove object metadata when saving SavedModel. by @copybara-service in #14697
  • Fix static shape inference for Resizing layer. by @copybara-service in #14712
  • Make TextVectorization work with list input. by @copybara-service in #14711
  • Remove deprecated methods of Sequential model. by @copybara-service in #14714
  • Improve Model docstrings by @copybara-service in #14726
  • Add migration doc for legacy_tf_layers/core.py. by @copybara-service in #14740
  • PR #43417: Fixes #42872: map_to_outputs_names always returns a copy by @copybara-service in #14755
  • Rename the keras.py to keras_lib.py to resolve the name conflict during OSS test. by @copybara-service in #14778
  • Switch to tf.io.gfile for validating vocabulary files. by @copybara-service in #14788
  • Avoid serializing generated thresholds for AUC metrics. by @copybara-service in #14789
  • Fix data_utils.py when name ends with .tar.gz by @copybara-service in #14777
  • Fix lookup layer oov token check when num_oov_indices > len(vocabulary tokens) by @copybara-service in #14793
  • Update callbacks.py by @jvishnuvardhan in #14760
  • Fix keras metric.result_state when the metric variables are sharded variable. by @copybara-service in #14790
  • Fix typos in CONTRIBUTING.md by @amogh7joshi in #14642
  • Fixed ragged sample weights by @DavideWalder in #14804
  • Pin the protobuf version to 3.9.2 which is same as the TF. by @copybara-service in #14835
  • Make variable scope shim regularizer adding check for attribute presence instead of instance class by @copybara-service in #14837
  • Add missing license header for leakr check. by @copybara-service in #14840
  • Fix TextVectorization with output_sequence_length on unknown input shapes by @copybara-service in #14832
  • Add more explicit error message for instance type checking of optimizer. by @copybara-service in #14846
  • Set aggregation for variable when using PS Strategy for aggregating variables when running multi-gpu tests. by @copybara-service in #14845
  • Remove unnecessary reshape layer in MobileNet architecture by @copybara-service in #14854
  • Removes caching of the convolution tf.nn.convolution op. While this provided some performance benefits, it also produced some surprising behavior for users in eager mode. by @copybara-service in #14855
  • Output int64 by default from Discretization by @copybara-service in #14841
  • add patterns to .gitignore by @haifeng-jin in #14861
  • Clarify documentation of DepthwiseConv2D by @vinhill in #14817
  • add DepthwiseConv1D layer by @fsx950223 in #14863
  • Make model summary wrap by @Llamrei in #14865
  • Update the link in Estimator by @hirobf10 in #14901
  • Fix int given for float args by @SamuelMarks in #14900
  • Fix RNN, StackedRNNCells with nested state_size, output_size TypeError issues by @Ending2015a in #14905
  • Fix the use of imagenet_utils.preprocess_input within a Lambda layer with mixed precision by @anth2o in #14917
  • Fix docstrings in MultiHeadAttention layer call argument return_attention_scores. by @guillesanbri in #14920
  • Check if layer has _metrics_lock attribute by @DanBmh in #14903
  • Make keras.Model picklable by @adriangb in #14748
  • Fix typo in docs by @seanmor5 in #14946
  • use getter setter by @fsx950223 in #14948
  • Close _SESSION.session in clear_session by @sfreilich in #14414
  • Fix keras nightly PIP package build. by @copybara-service in #14957
  • Fix EarlyStopping stop at fisrt epoch when patience=0 ; add auc to au… by @DachuanZhao in #14750
  • Add default value in Attention layer docs #50839 by @europeanplaice in #14952
  • Update 00-bug-template.md by @jvishnuvardhan in #14991
  • minor fixing by @slowy07 in #15008
  • Remove cast of y_true to y_pred data type in sparse categorical cross entropy loss by @old-school-kid in #15015
  • Improve a number of error messages in Keras layers. by @copybara-service in #15031
  • Fix typo in the test case name. by @copybara-service in #15050
  • BackupAndRestore callback: Allow the train_counter to be fault tolerant across training interruptions. by @copybara-service in #15018
  • Include Keras API design guidelines in the contribution docs. by @copybara-service in #15051
  • Fix clone_model to consider input_tensors by @LeonhardFeiner in #14982
  • Fix docs about GRU and cuDNN. by @bzamecnik in #15058
  • fix: typo spelling by @slowy07 in #14989
  • update contributing guide by @haifeng-jin in #15063
  • Make python code in Sequential docs consistent by @01-vyom in #15075
  • Create stale.yml by @rthadur in #15176
  • Update Contributing Guide by @haifeng-jin in #15133
  • fix "rbg" -> "rgb" in image_dataset_from_directory by @YoniChechik in #15177
  • Do not initialize tables automatically for lookup layers by @copybara-service in #15193
  • Log the best epoch when restoring the best weights in early stopping by @harupy in #15197
  • update contributing guide by @haifeng-jin in #15189
  • fix array for numpy support by @collinzrj in #15201
  • Add test case for batch normalization with renorm on TPUs. by @copybara-service in #15234
  • Update training.py by @jvishnuvardhan in #15195
  • [Follow-up for #15197] Fix a log message for weight restoration in early stopping by @harupy in #15222
  • Rename references to "K" as "backend" for consistency. by @copybara-service in #15242
  • Add Keras utility for making user programs deterministic. by @copybara-service in #15243
  • Update convolutional.py by @ymodak in #15158
  • Fix for bug causing failing test keras/utils/vis_utils_test.py test_layer_range_value_fail second value (empty list). by @ddrakard in #15215
  • Fix small mistake … optimizer to optimizers by @MohamedAliRashad in #15227
  • Added dense_shape property delegation by @jackd in #15199
  • handle when a List is used as validation_data instead of a Tuple, in model.fit() by @tarun-bisht in #15237
  • fix cropping layer return empty list if crop is higher than data shape by @arubiales in #14970
  • Make the import in integration_test consistent with other keras code. by @copybara-service in #15275
  • Specify stacklevel for warnings.warn to make it easier to identify which lines throw warnings by @harupy in #15209
  • Fixes Github tensorflow/issues/51710 by @copybara-service in #15280
  • Print expanded nested layers feature in models.summary() by @krishrustagi in #15251
  • adapt EarlyStopping auto mode to auc by @DachuanZhao in #15200
  • change misleading description of m_mul by @mikael-epigram in #15288
  • The latest update.Hope it can suit you by @DLPerf in #15295
  • Fixed and added ValueError for plot_model, model_to_dot and model.summary() by @krishrustagi in #15318
  • Fix a minor typo in CIFAR-10 and CIFAR-100 description by @Rishit-dagli in #15321
  • Fix cropping2D empty list #15325 by @arubiales in #15326
  • convert label_smoothing dtype to y dtype by @FancyXun in #15363
  • Exclude default bazel paths for VsCode by @bhack in #15343
  • fix: typo in SeparableConv1D by @carmineds in #15370
  • Add user bin path for pip installed packages by @bhack in #15385
  • Fix reset_metrics by @bhack in #15342
  • Kernel_size, pool_size should be positive integers by @WingsBrokenAngel in #15356
  • Reopening #48000, #48491, #48610 from tensorflow/tensorflow by @AdityaKane2001 in #15315
  • expand_nested bug fix and changing model.summary style by @krishrustagi in #15355
  • unnecessary casting and condition removed by @cemsina in #15399
  • Bug fix for issue #15211, PR #15233 ("Plot model show activations") by @ddrakard in #15286
  • fix a bug: when use tf.keras.layers.TextVectorization layer to load model by @mikuh in #15422
  • added correct initialisation for MHA by @FabianGroeger96 in #15423
  • Persist attribute "sparse" of IndexLookup layer by @diggerk in #15473
  • Updated Normalization import by @sachinprasadhs in #15476
  • Added layer trainable information in model summary by @mfidabel in #15459
  • Add efficientnet v2 to keras.applications by @sebastian-sz in #14935
  • Fix typos by @kianmeng in #15543
  • Update the contribution guide to include a applications section by @mattdangerw in #15447
  • chore: replace os.path.join with tf.io.gfile.join by @adriangb in #15551
  • Fixing typos. by @MohamadJaber1 in #15626
  • Updating the documentation of MAPE by @sanatmpa1 in #15604
  • Fix typo by @europeanplaice in #15639
  • [Docs] Changed typo ModelNetV3 to MobileNetV3. by @sebastian-sz in #15640
  • Adding a choice not to make batches in timeseries_dataset_from_array by @europeanplaice in #15646
  • Bypass the require a config warning for marge layers by @leondgarse in #15612
  • Allow keras.utils.Sequence sub-classes to use sparse/ragged tensors by @karlhigley in #15264
  • fix backend _GRAPH_LEARNING_PHASES graph circular reference. by @zhjunqin in #15520
  • doc: add link to SciKeras migration guide by @adriangb in #15723
  • Fix a minor typo in the docstring by @kykim0 in #15683
  • Fixed docstrings in keras/optimizer_v2/learning_rate_schedule.py by @AdityaKane2001 in #15718
  • Implement compute_output_shape for BaseDenseAttention by @mishc9 in #15720
  • SidecarEvaluator: Graduate from experimental endpoint. by @copybara-service in #15788
  • Update README.md by @aliencaocao in #15814
  • Update_OptimizerV2.py by @sachinprasadhs in #15819
  • Use assign_sub when computing moving_average_update by @lgeiger in #15773
  • Document the verbose parameter in EarlyStopping by @ThunderKey in #15817
  • Fix LSTM and GRU cuDNN kernel failure for RaggedTensors. by @foxik in #15756
  • A tiny problem in an AttributeError message in base_layer.py by @Aujkst in #15847
  • Update training_generator_test.py by @sachinprasadhs in #15876
  • Minor correction in RegNet docs by @AdityaKane2001 in #15901
  • add scoring methods in Luong-style attention by @old-school-kid in #15867
  • refactoring code with List Comprehension by @idiomaticrefactoring in #15924
  • added clarifying statement to save_model example text by @soosung80 in #15930
  • Update base_conv.py by @AdityaKane2001 in #15943
  • Update global_clipnorm by @sachinprasadhs in #15938
  • Update callbacks.py by @Cheril311 in #15977
  • Applied correct reshaping to metric func sparse_top_k by @dfossl in #15997
  • Keras saving/loading: Add a custom object saving test to verify the keras.utils.register_keras_serializable flows we are expecting users to follow work, and will continue to work with the new design and implementation coming in. by @copybara-service in #15992
  • Metric accuracy bug fixes - Metrics Refactor proposal by @dfossl in #16010
  • Make classifier_activation argument accessible for DenseNet and NASNet models by @adrhill in #16005
  • Copy image utils from keras_preprocessing directly into core keras by @copybara-service in #15975
  • Update keras.callbacks.BackupAndRestore docs by @lgeiger in #16018
  • Updating the definition of an argument in the text_dataset_from_directory function by @shraddhazpy in #16012
  • Remove deprecated TF1 Layer APIs apply(), get_updates_for(), get_losses_for(), and remove the inputs argument in the add_loss() method. by @copybara-service in #16046
  • Fixed minor typos by @hdubbs in #16071
  • Fix typo in documentation by @futtetennista in #16082
  • Issue #16090: Split input_shapes horizontally in utils.vis_utils.plot_model by @RicardFos in #16096
  • Docker env setup related changes by @shraddhazpy in #16040
  • Fixed EfficientNetV2 b parameter not increasing with each block. by @sebastian-sz in #16145
  • Updated args of train_on_batch method by @jvishnuvardhan in #16147
  • Binary accuracy bug fixes - Metric accuracy method refactor by @dfossl in #16083
  • Fix the corner case for dtensor model layout map. by @copybara-service in #16170
  • Fix typo in docstring for DenseFeatures by @gadagashwini in #16165
  • Fix typo in Returns Section by @chunduriv in #16182
  • Some tests misusing assertTrue for comparisons fix by @code-review-doctor in #16073
  • Add .DS_Store to .gitignore for macOS users by @tsheaff in #16198
  • Solve memory inefficiency in RNNs by @atmguille in #16174
  • Update README.md by @ahmedopolis in #16259
  • Fix documentation text being mistakenly rendered as code by @guberti in #16253
  • Allow single input for merging layers Add, Average, Concatenate, Maximum, Minimum, Multiply by @foxik in #16230
  • Mention image dimensions format in image_dataset_from_directory by @nrzimmermann in #16232
  • fix thresholded_relu to support list datatype by @old-school-kid in #16277
  • Implement all tf interpolation upscaling methods by @Mahrkeenerh in #16249
  • Fix TypeError positional argument when LossScalerOptimizer is used conjointly with tfa wrappers by @lucasdavid in #16332
  • Add type check to axis by @sachinprasadhs in #16208
  • minor documention fix by @bmatschke in #16331
  • Fix typos in data_adapter.py by @taegeonum in #16326
  • Add exclude_from_weight_decay to AdamW by @markub3327 in #16274
  • Switching learning/brain dependency to OSS compatible test_util by @copybara-service in #16362
  • Typo fix in LSTM docstring by @peskaf in #16364
  • Copy loss and metric to prevent side effect by @drauh in #16360
  • Denormalization layer by @markub3327 in #16350
  • Fix reset_states not working when invoked within a tf.function in graph mode. by @copybara-service in #16400
  • Reduce the complexity of the base layer by pulling out the logic related to handling call function args to a separate class. by @copybara-service in #16375
  • Add subset="both" functionality to {image|text}_dataset_from_directory() by @Haaris-Rahman in #16413
  • Fix non-float32 efficientnet calls by @hctomkins in #16402
  • Fix prediction with structured output by @itmo153277 in #16408
  • Add reference to resource variables. by @sachinprasadhs in #16409
  • added audio_dataset.py by @hazemessamm in #16388
  • Fix Syntax error for combined_model.compile of WideDeepModel by @gadagashwini in #16447
  • Missing f prefix on f-strings fix by @code-review-doctor in #16459
  • Update CONTRIBUTING.md by @rthadur in #15998
  • adds split_dataset utility by @prakashsellathurai in #16398
  • Support increasing batch size by @markus-hinsche in #16337
  • Add ConvNeXt models by @sayakpaul in #16421
  • Fix OrthogonalRegularizer to implement the (1,1) matrix norm by @Kiwiakos in #16521
  • fix: weight keys so that imagenet init works by @sayakpaul in #16528
  • Preprocess input correction by @AdityaKane2001 in #16527
  • Fix typo in documentation by @sushreebarsa in #16534
  • Update index_lookup.py by @tilakrayal in #16460
  • update codespaces bazel install by @haifeng-jin in #16575
  • reduce too long lines in engine/ by @haifeng-jin in #16579
  • Fix typos by @eltociear in #16568
  • Fix mixed precision serialization of group convs by @lgeiger in #16571
  • reduce layers line-too-long by @haifeng-jin in #16580
  • resolve line-too-long in root directory by @haifeng-jin in #16584
  • resolve line-too-long in metrics by @haifeng-jin in #16586
  • resolve line-too-long in optimizers by @haifeng-jin in #16587
  • resolve line-too-long in distribute by @haifeng-jin in #16594
  • resolve line-too-long in integration_test by @haifeng-jin in #16599
  • resovle line-too-long in legacy-tf-layers by @haifeng-jin in #16600
  • resolve line-too-long in initializers by @haifeng-jin in #16598
  • resolve line-too-long in api by @haifeng-jin in #16592
  • resolve line-too-long in benchmarks by @haifeng-jin in #16593
  • resolve line-too-long in feature_column by @haifeng-jin in #16597
  • resolve line-too-long in datasets by @haifeng-jin in #16591
  • resolve line-too-long in dtensor by @haifeng-jin in #16595
  • resolve line-too-long in estimator by @haifeng-jin in #16596
  • resolve line-too-long in applications by @haifeng-jin in #16590
  • resolve line-too-long in mixed_precision by @haifeng-jin in #16605
  • resolve line-too-long in models by @haifeng-jin in #16606
  • resolve line-too-long in premade_models by @haifeng-jin in #16608
  • resolve line-too-long in tests by @haifeng-jin in #16613
  • resolve line-too-long in testing_infra by @haifeng-jin in #16612
  • resolve line-too-long in saving by @haifeng-jin in #16611
  • resolve line-too-long in preprocessing by @haifeng-jin in #16609
  • resolve line-too-long in utils by @haifeng-jin in #16614
  • Optimize L2 Regularizer (use tf.nn.l2_loss) by @szutenberg in #16537
  • let the linter ignore certain lines, prepare to enforce line length by @haifeng-jin in #16617
  • Fix typo by @m-ahmadi in #16607
  • Explicitely set AutoShardPolicy.DATA for TensorLike datasets by @lgeiger in #16604
  • Fix all flake8 errors by @haifeng-jin in #16621
  • Update lint.yml by @haifeng-jin in #16648
  • Fix typo error of tf.compat.v1.keras.experimental for export and load model by @gadagashwini in #16636
  • Fix documentation in keras.datasets.imdb by @luckynozomi in #16673
  • Update init.py by @Wehzie in #16557
  • Fix documentation in keras.layers.attention.multi_head_attention by @balvisio in #16683
  • Fix missed parameter from AUC config by @weipeilun in #16499
  • Fix bug for KerasTensor._keras_mask should be None by @haifeng-jin in #16689
  • Fixed some spellings by @synandi in #16693
  • Fix batchnorm momentum in ResNetRS by @shkarupa-alex in #16726
  • Add variable definitions in optimizer usage example by @miker2241 in #16731
  • Fixed issue #16749 by @asukakenji in #16751
  • Fix usage of deprecated Pillow interpolation methods by @neoaggelos in #16746
  • 📝 Add typing to some callback classes by @gabrieldemarmiesse in #16692
  • Add support for Keras mask & causal mask to MultiHeadAttention by @ageron in #16619
  • Update standard name by @chunduriv in #16772
  • Fix error when labels contains brackets when plotting model by @cBournhonesque in #16739
  • Fixing the incorrect link in input_layer.py by @tilakrayal in #16767
  • Formatted callback.py to render correctly by @jvishnuvardhan in #16765
  • Fixed typo in docs by @ltiao in #16778
  • docs: Fix a few typos by @timgates42 in #16789
  • Add ignore_class to sparse crossentropy and IoU by @lucasdavid in #16712
  • Updated f-string method by @cyai in #16799
  • Fix NASNet input shape computation by @ianstenbit in #16818
  • Fix incorrect ref. to learning_rate_schedule during module import by @lucasdavid in #16813
  • Fixing the incorrect link in backend.py by @tilakrayal in #16806
  • Corrected DepthwiseConv1D docstring by @AdityaKane2001 in #16807
  • Typo and grammar: "recieved" by @ehrencrona in #16814
  • Fix typo in doc by @DyeKuu in #16821
  • Update README.md by @freddy1020 in #16823
  • Updated f-string method by @cyai in #16775
  • Add is_legacy_optimizer to optimizer config to keep saving/loading consistent. by @copybara-service in #16842
  • Add is_legacy_optimizer to optimizer config to keep saving/loading … by @qlzh727 in #16856

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