Tensorflow

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0.5.0

Initial release of TensorFlow.

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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.
* Add `ConcatenateDataset` to concatenate two datasets.
* Added Mobilenet support to TensorFlow for Poets training script.
* Adds a block cache to the GCS filesystem with configurable block size and
count.
* SinhArcSinh bijector added.
* Added `Dataset.list_files` API.
* Introduces new operations and Python bindings for the Cloud TPU.
* Adding TensorFlow-iOS CocoaPod for symmetry with tensorflow-android.
* Introduces base implementations of ClusterResolvers.
* Unify memory representations of TensorShape and PartialTensorShape. As a
consequence, tensors now have a maximum of 254 dimensions, not 255.
* Changed references to LIBXSMM to use version 1.8.1.
* TensorFlow Debugger (tfdbg):
* Display summaries of numeric tensor values with the `-s` flag to command
`print_tensor` or `pt`.
* Display feed values with the `print_feed` or `pf` command and clickable
links in the curses UI.
* Runtime profiler at the op level and the Python source line level with
the `run -p` command.
* Initial release of the statistical distribution library `tf.distributions`.
* GPU kernels and speed improvements for unary `tf.where` and `tf.nn.top_k`.
* Monotonic Attention wrappers added to `tf.contrib.seq2seq`.
* Added `tf.contrib.signal`, a library for signal processing primitives.
* Added `tf.contrib.resampler`, containing CPU and GPU ops for differentiable
resampling of images.

Breaking Changes to the API

* `tf.RewriterConfig` was removed from the Python API after being available in

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