0.1.3 release preparation.

PiperOrigin-RevId: 265144137

Author: alanchiao

README.md

@@ -25,9 +25,10 @@ pip install --user --upgrade tensorflow-model-optimization
 For release details, see our
 [release notes](https://github.com/tensorflow/model-optimization/releases).
 
-TensorFlow Model Optimization currently depends on the nightly build of
-[TensorFlow](https://www.tensorflow.org/install) (pip package `tf-nightly`) and
-only supports Tensorflow 1.XX.
+TensorFlow Model Optimization requires either Tensorflow 1.x for versions 1.14+
+or the nightly build of [TensorFlow](https://www.tensorflow.org/install) (pip
+package `tf-nightly`). Note that for the nightly build, you need to use
+tf.compat.v1 since 2.x is the default now.
 
 Since TensorFlow is *not* included as a dependency of the TensorFlow Model
 Optimization package (in `setup.py`), you must explicitly install the TensorFlow

tensorflow_model_optimization/g3doc/_project.yaml

@@ -1,5 +1,5 @@
 name: TensorFlow model optimization
-breadcrumb_name: Model optimization v0.1.2
+breadcrumb_name: Model optimization v0.1.3
 home_url: /model_optimization/
 parent_project_metadata_path: /_project.yaml
 description: >

tensorflow_model_optimization/g3doc/guide/pruning/index.md

@@ -23,12 +23,14 @@ speech recognition and text-to-speech, and has been experimented on across
 various vision and translation models.
 
 Users can apply this technique using APIs for Keras on Tensorflow 1.x for
-versions 1.14+ and nightly in both graph and eager execution.
+versions 1.14+ and tf-nightly in both graph and eager execution. Note that in
+tf-nightly, you must use tf.compat.v1 since 2.x is the default now.
 
 Note: The pruning API is only compatible with `tf.distribute` when using graph
-execution. It is on our roadmap to bring full support to TF 2.x and eager
 execution.
 
+It is on our roadmap to bring full support to TF 2.x and eager execution.
+
 ## Results
 
 ### Image Classification

tensorflow_model_optimization/g3doc/guide/pruning/pruning_with_keras.ipynb

@@ -120,7 +120,10 @@
         "id": "q8zIQsT9mUTw"
       },
       "source": [
-        "To use the pruning API, you need to install the `tensorflow-model-optimization` and `tf-nightly` packages.\n",
+        "To use the pruning API, you need to install the
+	`tensorflow-model-optimization` package. See
+	https://github.com/tensorflow/model-optimization for what versions of
+	TensorFlow the API is compatible with.\n",
         "\n",
         "Since you will train a few models in this tutorial, install the `tensorflow-gpu` package to speed up things. Enable the GPU with: *Runtime \u003e Change runtime type \u003e Hardware accelator* and make sure GPU is selected."
       ]
@@ -137,7 +140,7 @@
       "source": [
         "! pip uninstall -y tensorflow\n",
         "! pip uninstall -y tf-nightly\n",
-        "! pip install -U tf-nightly-gpu\n",
+        "! pip install -U tensorflow-gpu==1.14.0\n",
         "\n",
         "! pip install tensorflow-model-optimization"
       ]

tensorflow_model_optimization/python/core/version.py

@@ -17,7 +17,7 @@
 # We follow Semantic Versioning (https://semver.org/)
 _MAJOR_VERSION = '0'
 _MINOR_VERSION = '1'
-_PATCH_VERSION = '2'
+_PATCH_VERSION = '3'
 
 # When building releases, we can update this value on the release branch to
 # reflect the current release candidate ('rc0', 'rc1') or, finally, the official