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Sonnet Changelog

Version 1.15 - Monday, 20. November 2017

  • sonnet.nest *iterable functions now point to their equivalent from TF.
  • Small documentation changes.
  • Add custom_getter option to sonnet.Embed.

Version 1.14 - Thursday, 09. November 2017

This version requires TensorFlow version 1.4.0.

  • Switch parameterized tests to use Abseil.
  • BatchApply passes through scalar non-Tensor inputs unmodified.
  • More flexible mask argument to Conv2D.
  • Added Sonnet ModuleInfo to the "sonnet" graph collection. This allows to keep track of which modules generated which connected sub-graphs. This information is serialised and available when loading a meta-graph-def. This can be used, for instance, to visualise the TensorFlow graph from a Sonnet perspective.
  • Scale_gradient now handles all float dtypes.
  • Fixed a bug in clip_gradient that caused clip values to be shared.
  • ConvNet can now use the NCHW data format.
  • Cleaned up and improved example text for snt.custom_getters.Context.

Version 1.13 - Monday 25. Septebmer 2017

  • Separate BatchNormLSTM and LSTM to two separate modules.
  • Clarify example in Readme.

Version 1.12 - Monday 18. September 2017

  • custom_getters subpackage. This allows modules to be made non-trainable, or to completely block gradients. See documentation for tf.get_variable for more details.
  • Sequential.get_variables() generates a warning to indicate that no variables will ever be returned.
  • ConvLSTM now supports dilated convolutions.
  • utils.format_variables allows logging Variables with non-static shape.
  • snt.trainable_initial_state is now publicly exposed.
  • Stop using private property of tf.Graph in util.py.

Version 1.11 - Monday 21. August 2017

This version requires TensorFlow 1.3.0.

  • Backwards incompatible change: Resampler ops removed, they are now available in tf.contrib.resampler.
  • Custom getters supported in RNNs and AlexNet.
  • Replace last references to contrib.RNNCell with snt.RNNCore.
  • Removed Tensorflow dependencies in Bazel config files, which makes it unnecessary to have Tensorflow as a submodule of Sonnet.

Version 1.10 - Monday, 14. August 2017

  • First steps of AlexNet cleanup.
    • Add option to disable batch normalization on fully-connected layers.
    • Remove HALF mode.
    • Add AlexNetMini and AlexNetFull.
  • Fixed bias compatibility between NHWC and NCHW data formats in Conv2D. Uses tf.nn.bias_add for bias addition in all convolutional layers.
  • snt.BatchApply now also accepts scalar-valued inputs such as Boolean flags.

Version 1.9 - Monday 7. August 2017

  • Clean up and clarify documentation on nest's dict ordering behavior.
  • Change installation instructions to use pip.

Version 1.8 - Monday 31. July 2017

  • Add optional bias for the multipler in AddBias.
  • Push first version of wheel files to PyPI.

Version 1.7 - Monday 24. July 2017

  • Fix install script for Python 3.
  • Better error message in AbstractModule.
  • Fix out of date docs about RNNCore.
  • Use tf.layers.utils instead of tf.contrib.layers.utils, allowing to remove the use of contrib in the future, which will save on import time.
  • Fixes to docstrings.

Version 1.6 - Monday, 17. July 2017

  • Support "None" entries in BatchApply's inputs.
  • Add custom_getter option to convolution modules and MLP.
  • Better error messages for BatchReshape.

Version 1.5 - Monday, 10. July 2017

  • install.sh now supports relative paths as well as absolute.
  • Accept string values as variable scope in snt.get_variables_in_scope and snt.get_normalized_variable_map.
  • Add IPython notebook that explains how Sonnet's BatchNorm module can be configured.

Version 1.4 - 3rd Jul 2017

  • Added all constructor arguments to ConvNet2D.transpose and ConvNet2DTranspose.transpose.
  • Backwards incompatible change is_training flags of _build functions no longer default to True. They must be specified explicitly at every connection point.
  • Added causal 1D Convolution.
  • Fixed to scope name utilities.
  • Added flatten_dict_items to snt.nest.
  • Conv1DTranspose modules can accept input with undefined batch sizes.
  • Apply verification to output_shape in ConvTranspose modules.

Version 1.3 - 26th Jun 2017

This version is only compatible with TensorFlow 1.2.0, not the current GitHub HEAD.

  • Resampler op now tries to import from tf.contrib first and falls back to the Sonnet op. This is in preparation for the C++ ops to be moved into tf/contrib.
  • snt.RNNCore no longer inherits from tf.RNNCell. All recurrent modules will continue to be suppoted by tf.dynamic_rnn, tf.static_rnn, etc.
  • The ability to add a custom_getter to a module is now supported by snt.AbstractModule. This is currently only available in snt.Linear, with more to follow. See the documentation for tf.get_variable for how to use custom_getters.
  • Documentation restructured.
  • Some functions and tests reorganised.

Version 1.2 - 19th Jun 2017

  • Cell & Hidden state clipping added to LSTM.
  • Added Makefile for generating documentation with Sphinx.
  • Batch Norm options for LSTM now deprecated to a separate class BatchNormLSTM. A future version of LSTM will no longer contain the batch norm flags.
  • @snt.experimental.reuse_vars decorator promoted to @snt.reuse_variables.
  • BatchReshape now takes a preserve_dims parameter.
  • DeepRNN prints a warning if the heuristic is used to infer output size.
  • Deprecated properties removed from AbstractModule.
  • Pass inferred data type to bias and weight initializers.
  • AlexNet now checks that dropout is disabled or set to 1.0 when testing.
  • .get_saver() now groups partitioned variables by default.
  • Docstring, variable name and comment fixes.

Version 1.1 - 12th Jun 2017

  • breaking change: Calling AbstractModule.__init__ with positional arguments is now not supported. All calls to __init__ should be changed to use kwargs. This change will allow future features to be added more easily.
  • Sonnet modules now throw an error if pickled. Instead of serializing module instances, you should serialize the constructor you want to call, plus the arguments you would pass it, and recreate the module instances in each run of the program.
  • Sonnet no longer allows the possibility that self._graph does not exist. This would only be the case when reloading pickle module instances, which is not supported.
  • Fix tolerance on initializers_test.
  • If no name is passed to the AbstractModule constructor, a snake_case version of the class name will be used.
  • _build() now checks that __init__ has been called first and throws an error otherwise.
  • Residual and Skip connection RNN wrapper cores have been added.
  • get_normalized_variable_map() now has an option to group partitioned variables, matching what tf.Saver expects.
  • snt.BatchApply now support kwargs, nested dictionaries, and allows None to be returned.
  • Add a group_sliced_variables option to get_normalized_variable_map() that groups partitioned variables in its return value, in line with what tf.Saver expects to receive. This ensures that partitioned variables end up being treated as a unit when saving checkpoints / model snapshots with tf.Saver. The option is set to False by default, for backwards compatibility reasons.
  • snt.Linear.transpose creates a new module which now uses the same partitioners as the parent module.