Increment version and add release notes for TFF 0.6.0.

PiperOrigin-RevId: 255260630

README.md

@@ -88,6 +88,7 @@ versions.
 TensorFlow Federated                                         | TensorFlow
 ------------------------------------------------------------ | ----------
 [master](https://github.com/tensorflow/federated)            | [tf-nightly 1.x](https://pypi.org/project/tf-nightly/)
+[0.6.0](https://github.com/tensorflow/federated/tree/v0.5.0) | [tf-nightly 1.15.0.dev20190626](https://pypi.org/project/tf-nightly/1.15.0.dev20190626/)
 [0.5.0](https://github.com/tensorflow/federated/tree/v0.5.0) | [tf-nightly 1.14.1.dev20190528](https://pypi.org/project/tf-nightly/1.14.1.dev20190528/)
 [0.4.0](https://github.com/tensorflow/federated/tree/v0.4.0) | [tensorflow 1.13.1](https://pypi.org/project/tensorflow/1.13.1)
 [0.3.0](https://github.com/tensorflow/federated/tree/v0.3.0) | [tensorflow 1.13.1](https://pypi.org/project/tensorflow/1.13.1)

RELEASE.md

+# Release 0.6.0
+
+## Major Features and Improvements
+
+*   Support for multiple outputs and loss functions in `keras` models.
+*   Support for stateful broadcast and aggregation functions in federated
+    averaging and federated SGD APIs.
+*   `tff.utils.update_state` extended to handle more general `state` arguments.
+*   Addition of `tff.utils.federated_min` and `tff.utils.federated_max`.
+*   Shuffle `client_ids` in `create_tf_dataset_from_all_clients` by default to
+    aid optimization.
+
+## Breaking Changes
+
+*   Dependencies added to `requirements.txt`; in particular, `grpcio` and
+    `portpicker`.
+
+## Bug Fixes
+
+*   Removes dependency on `tf.data.experimental.NestedStructure`.
+
+## Thanks to our Contributors
+
+This release contains contributions from many people at Google, as well as:
+
+Dheeraj R Reddy, @Squadrick.
+
 # Release 0.5.0
 
 ## Major Features and Improvements
 
-* Removed source level TF dependencies and switched from `tensorflow` to
-  `tf-nightly` dependency.
-* Add support for `attr` module in TFF type system.
-* Introduced new `tff.framework` interface layer.
-* New AST transformations and optimizations.
-* Preserve Python container usage in `tff.tf_computation`.
+*   Removed source level TF dependencies and switched from `tensorflow` to
+    `tf-nightly` dependency.
+*   Add support for `attr` module in TFF type system.
+*   Introduced new `tff.framework` interface layer.
+*   New AST transformations and optimizations.
+*   Preserve Python container usage in `tff.tf_computation`.
 
 ## Bug Fixes
 
-* Updated TFF model to reflect Keras `tf.keras.model.weights` order.
-* Keras model with multiple inputs. #416
+*   Updated TFF model to reflect Keras `tf.keras.model.weights` order.
+*   Keras model with multiple inputs. #416
 
 # Release 0.4.0
 
 ## Major Features and Improvements
 
-* New `tff.simulation.TransformingClientData` API and associated inifinite
-  EMNIST dataset (see http://tensorflow.org/federated/api_docs/python/tff for
-  details)
+*   New `tff.simulation.TransformingClientData` API and associated inifinite
+    EMNIST dataset (see http://tensorflow.org/federated/api_docs/python/tff for
+    details)
 
 ## Breaking Change
 
-* Normalized `func` to `fn` across the repository (rename some parameters and
-  functions)
+*   Normalized `func` to `fn` across the repository (rename some parameters and
+    functions)
 
 ## Bug Fixes
 
-* Wrapped Keras models can now be used with
-  `tff.learning.build_federated_evaluation`
-* Keras models with non-trainable variables in intermediate layers (e.g.
-  BatchNormalization) can be assigned back to Keras models with
-  `tff.learning.ModelWeights.assign_weights_to`
+*   Wrapped Keras models can now be used with
+    `tff.learning.build_federated_evaluation`
+*   Keras models with non-trainable variables in intermediate layers (e.g.
+    BatchNormalization) can be assigned back to Keras models with
+    `tff.learning.ModelWeights.assign_weights_to`
 
 # Release 0.3.0
 
 ## Breaking Changes
 
-* Rename `tff.learning.federated_average` to `tff.learning.federated_mean`.
-* Rename 'func' arguments to 'fn' throughout the API.
+*   Rename `tff.learning.federated_average` to `tff.learning.federated_mean`.
+*   Rename 'func' arguments to 'fn' throughout the API.
 
 ## Bug Fixes
 
-* Assorted fixes to typos in documentation and setup scripts.
+*   Assorted fixes to typos in documentation and setup scripts.
 
 # Release 0.2.0
 
 ## Major Features and Improvements
 
-* Updated to use TensorFlow version 1.13.1.
-* Implemented Federated SGD in `tff.learning.build_federated_sgd_process()`.
+*   Updated to use TensorFlow version 1.13.1.
+*   Implemented Federated SGD in `tff.learning.build_federated_sgd_process()`.
 
 ## Breaking Changes
 
-* `next()` function of `tff.utils.IteratedProcess`s returned by
-  `build_federated_*_process()` no longer unwraps single value tuples
-  (always returns a tuple).
+*   `next()` function of `tff.utils.IteratedProcess`s returned by
+    `build_federated_*_process()` no longer unwraps single value tuples (always
+    returns a tuple).
 
 ## Bug Fixes
 
-* Modify setup.py to require TensorFlow 1.x and not upgrade to 2.0 alpha.
-* Stop unpacking single value tuples in `next()` function of objects returned by
-  `build_federated_*_process()`.
-* Clear cached Keras sessions when wrapping Keras models to avoid referencing
-  stale graphs.
+*   Modify setup.py to require TensorFlow 1.x and not upgrade to 2.0 alpha.
+*   Stop unpacking single value tuples in `next()` function of objects returned
+    by `build_federated_*_process()`.
+*   Clear cached Keras sessions when wrapping Keras models to avoid referencing
+    stale graphs.
 
 # Release 0.1.0
 

docs/tutorials/custom_federated_algorithms_1.ipynb

@@ -27,14 +27,14 @@
 <table class="tfo-notebook-buttons" align="left">
   <td>
     <a target="_blank" href="https://www.tensorflow.org/federated/tutorials/custom_federated_algorithms_1"><img src="https://www.tensorflow.org/images/tf_logo_32px.png" />View on TensorFlow.org</a>
   </td>
   <td>
-    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.5.0/docs/tutorials/custom_federated_algorithms_1.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
+    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.6.0/docs/tutorials/custom_federated_algorithms_1.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
   </td>
   <td>
-    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.5.0/docs/tutorials/custom_federated_algorithms_1.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
+    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.6.0/docs/tutorials/custom_federated_algorithms_1.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
   </td>
 </table>
 
 %% Cell type:markdown id: tags:
 

docs/tutorials/custom_federated_algorithms_2.ipynb

@@ -27,14 +27,14 @@
 <table class="tfo-notebook-buttons" align="left">
   <td>
     <a target="_blank" href="https://www.tensorflow.org/federated/tutorials/custom_federated_algorithms_2"><img src="https://www.tensorflow.org/images/tf_logo_32px.png" />View on TensorFlow.org</a>
   </td>
   <td>
-    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.5.0/docs/tutorials/custom_federated_algorithms_2.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
+    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.6.0/docs/tutorials/custom_federated_algorithms_2.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
   </td>
   <td>
-    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.5.0/docs/tutorials/custom_federated_algorithms_2.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
+    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.6.0/docs/tutorials/custom_federated_algorithms_2.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
   </td>
 </table>
 
 %% Cell type:markdown id: tags:
 

docs/tutorials/federated_learning_for_image_classification.ipynb

@@ -27,20 +27,20 @@
 <table class="tfo-notebook-buttons" align="left">
   <td>
     <a target="_blank" href="https://www.tensorflow.org/federated/tutorials/federated_learning_for_image_classification"><img src="https://www.tensorflow.org/images/tf_logo_32px.png" />View on TensorFlow.org</a>
   </td>
   <td>
-    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.5.0/docs/tutorials/federated_learning_for_image_classification.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
+    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.6.0/docs/tutorials/federated_learning_for_image_classification.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
   </td>
   <td>
-    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.5.0/docs/tutorials/federated_learning_for_image_classification.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
+    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.6.0/docs/tutorials/federated_learning_for_image_classification.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
   </td>
 </table>
 
 %% Cell type:markdown id: tags:
 
-**NOTE**: This colab has been verified to work with the `0.5.0` version of the `tensorflow_federated` pip package, but the Tensorflow Federated project is still in pre-release development and may not work on `master`.
+**NOTE**: This colab has been verified to work with the `0.6.0` version of the `tensorflow_federated` pip package, but the Tensorflow Federated project is still in pre-release development and may not work on `master`.
 
 In this tutorial, we use the classic MNIST training example to introduce the
 Federated Learning (FL) API layer of TFF, `tff.learning` - a set of
 higher-level interfaces that can be used to perform common types of federated
 learning tasks, such as federated training, against user-supplied models

docs/tutorials/federated_learning_for_text_generation.ipynb

@@ -27,20 +27,20 @@
 <table class="tfo-notebook-buttons" align="left">
   <td>
     <a target="_blank" href="https://www.tensorflow.org/federated/tutorials/federated_learning_for_text_generation"><img src="https://www.tensorflow.org/images/tf_logo_32px.png" />View on TensorFlow.org</a>
   </td>
   <td>
-    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.5.0/docs/tutorials/federated_learning_for_text_generation.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
+    <a target="_blank" href="https://colab.research.google.com/github/tensorflow/federated/blob/v0.6.0/docs/tutorials/federated_learning_for_text_generation.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />Run in Google Colab</a>
   </td>
   <td>
-    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.5.0/docs/tutorials/federated_learning_for_text_generation.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
+    <a target="_blank" href="https://github.com/tensorflow/federated/blob/v0.6.0/docs/tutorials/federated_learning_for_text_generation.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" />View source on GitHub</a>
   </td>
 </table>
 
 %% Cell type:markdown id: tags:
 
-**NOTE**: This colab has been verified to work with the `0.5.0` version of the `tensorflow_federated` pip package, but the Tensorflow Federated project is still in pre-release development and may not work on `master`.
+**NOTE**: This colab has been verified to work with the `0.6.0` version of the `tensorflow_federated` pip package, but the Tensorflow Federated project is still in pre-release development and may not work on `master`.
 
 This tutorial builds on the concepts in the [Federated Learning for Image Classification](federated_learning_for_image_classification.md) tutorial, and demonstrates several other useful approaches for federated learning.
 
 In particular, we load a previously trained Keras model, and refine it using  federated training on a (simulated) decentralized dataset. This is practically important for several reasons . The ability to use serialized models makes it easy to mix federated learning with other ML approaches. Further, this allows use of an increasing range of pre-trained models --- for example, training language models from scratch is rarely necessary, as numerous pre-trained models are now widely available (see, e.g., [TF Hub](https://www.tensorflow.org/hub)). Instead, it makes more sense to start from a pre-trained model, and refine it using Federated Learning, adapting to the particular characteristics of the decentralized data for a particular application.
 

tensorflow_federated/tools/setup.py

@@ -56,7 +56,7 @@ import setuptools
 
 DOCLINES = __doc__.split('\n')
 
-_VERSION = '0.5.0'
+_VERSION = '0.6.0'
 
 project_name = 'tensorflow_federated'
 
@@ -72,6 +72,8 @@ REQUIRED_PACKAGES = [
     'numpy~=1.14',
     'six~=1.10',
     'tf-nightly',
+    'grpcio~=1.8.0',
+    'portpicker',
 ]
 
 setuptools.setup(