pypi keras 2.2.3
Keras 2.2.3

latest releases: 2.11.0, 2.11.0rc3, 2.11.0rc2...
4 years ago

Areas of improvement

  • API completeness & usability improvements
  • Bug fixes
  • Documentation improvements

API changes

  • Keras models can now be safely pickled.
  • Consolidate the functionality of the activation layers ThresholdedReLU and LeakyReLU into the ReLU layer.
  • As a result, the ReLU layer now takes new arguments negative_slope and threshold, and the relu function in the backend takes a new threshold argument.
  • Add update_freq argument in TensorBoard callback, controlling how often to write TensorBoard logs.
  • Add the exponential function to keras.activations.
  • Add data_format argument in all 4 Pooling1D layers.
  • Add interpolation argument in UpSampling2D layer and in resize_images backend function, supporting modes "nearest" (previous behavior, and new default) and "bilinear" (new).
  • Add dilation_rate argument in Conv2DTranspose layer and in conv2d_transpose backend function.
  • The LearningRateScheduler now receives the lr key as part of the logs argument in on_epoch_end (current value of the learning rate).
  • Make GlobalAveragePooling1D layer support masking.
  • The the filepath argument save_model and can now be a h5py.Group instance.
  • Add argument restore_best_weights to EarlyStopping callback (optionally reverts to the weights that obtained the highest monitored score value).
  • Add dtype argument to keras.utils.to_categorical.
  • Support run_options and run_metadata as optional session arguments in model.compile() for the TensorFlow backend.

Breaking changes

  • Modify the return value of Sequential.get_config(). Previously, the return value was a list of the config dictionaries of the layers of the model. Now, the return value is a dictionary with keys layers, name, and an optional key build_input_shape. The old config is equivalent to new_config['layers']. This makes the output of get_config consistent across all model classes.


Thanks to our 38 contributors whose commits are featured in this release:

@BertrandDechoux, @ChrisGll, @Dref360, @JamesHinshelwood, @MarcoAndreaBuchmann, @ageron, @alfasst, @blue-atom, @chasebrignac, @cshubhamrao, @danFromTelAviv, @datumbox, @farizrahman4u, @fchollet, @fuzzythecat, @gabrieldemarmiesse, @hadifar, @heytitle, @hsgkim, @jankrepl, @joelthchao, @knightXun, @kouml, @linjinjin123, @lvapeab, @nikoladze, @ozabluda, @qlzh727, @roywei, @rvinas, @sriyogesh94, @tacaswell, @taehoonlee, @tedyu, @xuhdev, @yanboliang, @yongzx, @yuanxiaosc

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