<commit_before># Release 1.4.0

## Major Features And Improvements

## Bug Fixes and Other Changes
* `tf.nn.rnn_cell.DropoutWrapper` is now more careful about dropping out LSTM
  states.  Specifically, it no longer ever drops the `c` (memory) state of an
  `LSTMStateTuple`.  The new behavior leads to proper dropout behavior
  for LSTMs and stacked LSTMs.  This bug fix follows recommendations from
  published literature, but is a behavioral change.  State dropout behavior
  may be customized via the new `dropout_state_filter_visitor` argument.
* Removed `tf.contrib.training.python_input`.  The same behavior, in a more
  flexible and reproducible package, is available via the new
  `tf.contrib.data.Dataset.from_generator` method!

# Release 1.3.0

See also [TensorBoard 0.1.4](https://github.com/tensorflow/tensorboard/releases/tag/0.1.4) release notes.

## Major Features and Improvements
* Added canned estimators to Tensorflow library. List of added estimators:
  * `DNNClassifier`
  * `DNNRegressor`
  * `LinearClassifier`
  * `LinearRegressor`
  * `DNNLinearCombinedClassifier`
  * `DNNLinearCombinedRegressor`.
* All our prebuilt binaries have been built with cuDNN 6. We anticipate releasing TensorFlow 1.4 with cuDNN 7.
* `import tensorflow` now goes much faster.
* Adds a file cache to the GCS filesystem with configurable max staleness for file contents. This permits caching of file contents across close/open boundaries.
* Added an axis parameter to `tf.gather`.
* Added a `constant_values` keyword argument to `tf.pad`.
* Adds `Dataset.interleave` transformation.<commit_msg>Java: Updated release notes to include some recent contributions.<commit_after># Release 1.4.0

## Major Features And Improvements
* Java:
  * Generics (e.g., `Tensor<Integer>`) for improved type-safety (courtesy @andrewcmyers).
  * Support for multi-dimensional string tensors.

## Bug Fixes and Other Changes
* `tf.nn.rnn_cell.DropoutWrapper` is now more careful about dropping out LSTM
  states.  Specifically, it no longer ever drops the `c` (memory) state of an
  `LSTMStateTuple`.  The new behavior leads to proper dropout behavior
  for LSTMs and stacked LSTMs.  This bug fix follows recommendations from
  published literature, but is a behavioral change.  State dropout behavior
  may be customized via the new `dropout_state_filter_visitor` argument.
* Removed `tf.contrib.training.python_input`.  The same behavior, in a more
  flexible and reproducible package, is available via the new
  `tf.contrib.data.Dataset.from_generator` method!

# Release 1.3.0

See also [TensorBoard 0.1.4](https://github.com/tensorflow/tensorboard/releases/tag/0.1.4) release notes.

## Major Features and Improvements
* Added canned estimators to Tensorflow library. List of added estimators:
  * `DNNClassifier`
  * `DNNRegressor`
  * `LinearClassifier`
  * `LinearRegressor`
  * `DNNLinearCombinedClassifier`
  * `DNNLinearCombinedRegressor`.
* All our prebuilt binaries have been built with cuDNN 6. We anticipate releasing TensorFlow 1.4 with cuDNN 7.
* `import tensorflow` now goes much faster.
* Adds a file cache to the GCS filesystem with configurable max staleness for file contents. This permits caching of file contents across close/open boundaries.
* Added an axis parameter to `tf.gather`.
* Added a `constant_values` keyword argument to `tf.pad`.
* Adds `Dataset.interleave` transformation.
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