Update release notes for TensorFlow 1.4

RELEASE.md

@@ -11,9 +11,37 @@
   * Several custom transformation functions have been added, including
     `tf.contrib.data.batch_and_drop_remainder()` and
     `tf.contrib.data.sloppy_interleave()`.
+* Add `train_and_evaluate` for simple distributed `Estimator` training.
+* Add `tf.spectral.dct` for computing the DCT-II.
+* Add Mel-Frequency Cepstral Coefficient support to `tf.contrib.signal`
+  (with GPU and gradient support).
+* Add a self-check on `import tensorflow` for Windows DLL issues.
+* Add NCHW support to `tf.depth_to_space` on GPU.
+* SinhArcsinh (scalar) distribution added to `contrib.distributions`.
+* Make `GANEstimator` opensource.
+* `Estimator.export_savedmodel()` now includes all valid serving signatures
+  that can be constructed from the Serving Input Receiver and all available
+  ExportOutputs. For instance, a classifier may provide regression- and
+  prediction-flavored outputs, in addition to the classification-flavored one.
+  Building signatures from these allows TF Serving to honor requests using the
+  different APIs (Classify, Regress, and Predict). Furthermore,
+  `serving_input_receiver_fn()` may now specify alternative subsets of nodes
+  that may act as inputs. This allows, for instance, producing a prediction
+  signature for a classifier that accepts raw `Tensors` instead of a serialized
+  `tf.Example`.
+* Add `tf.contrib.bayesflow.hmc`.
+* Add `tf.contrib.distributions.MixtureSameFamily`.
+* Make `Dataset.shuffle()` always reshuffles after each iteration by default.
+* Add `tf.contrib.bayesflow.metropolis_hastings`.
+* Add `log_rate` parameter to `tf.contrib.distributions.Poisson`.
+* Extend `tf.contrib.distributions.bijector` API to handle some non-injective
+  transforms.
 * Java:
-  * Generics (e.g., `Tensor<Integer>`) for improved type-safety (courtesy @andrewcmyers).
+  * Generics (e.g., `Tensor<Integer>`) for improved type-safety
+    (courtesy @andrewcmyers).
   * Support for multi-dimensional string tensors.
+  * Support loading of custom operations (e.g. many in `tf.contrib`) on Linux
+    and OS X
 
 ## Bug Fixes and Other Changes
 * `tf.nn.rnn_cell.DropoutWrapper` is now more careful about dropping out LSTM
@@ -25,11 +53,20 @@
 * 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!
+* Fix `tf.contrib.distributions.Affine` incorrectly computing log-det-jacobian.
+* Fix `tf.random_gamma` incorrectly handling non-batch, scalar draws.
+* Resolved a race condition in TensorForest TreePredictionsV4Op.
+* Google Cloud Storage file system and Hadoop file system support are now
+  default build options.
 
 ## Breaking Changes to the API
 * The signature of the `tf.contrib.data.rejection_resample()` function has been
   changed. It now returns a function that can be used as an argument to
   `Dataset.apply()`.
+* Remove `tf.contrib.data.Iterator.from_dataset()` method. Use
+  `Dataset.make_initializable_iterator()` instead.
+* Remove seldom used and unnecessary `tf.contrib.data.Iterator.dispose_op()`.
+* Reorder some TFGAN loss functions in a non-backwards compatible way.
 
 # Release 1.3.0