[Tensorflow] API 1.2 Releaseされました。

Tensorflow 1.2 Versionがアップデートされました。


# Release 1.2.0

## Major Features and Improvements
* Added `tf.layers.conv3d_transpose` layer for spatio temporal deconvolution.
* Added `tf.Session.make_callable()`, which provides a lower overhead means of running a similar step multiple times.
* Added ibverbs-based RDMA support to contrib (courtesy @junshi15 from Yahoo).
* `RNNCell` objects now subclass `tf.layers._Layer`.  The strictness described
  in the TensorFlow 1.1 release is gone:  The first time an RNNCell is used,
  it caches its scope.  All future uses of the RNNCell will reuse variables from
  that same scope.  This is a breaking change from the behavior of RNNCells
  in TensorFlow versions <= 1.0.1.  TensorFlow 1.1 had checks in place to
  ensure old code works correctly with the new semantics; this version
  allows more flexible uses of RNNCell but can lead to subtle errors if
  using code meant for TensorFlow <= 1.0.1.  For example, writing:
  `MultiRNNCell([lstm] * 5)` will now build a 5-layer LSTM stack where each
  layer shares the **same** parameters.  To get 5 layers each with their own
  parameters, write: `MultiRNNCell([LSTMCell(...) for _ in range(5)])`.
  If at all unsure, first test your code with TF 1.1; ensure it raises no
  errors, and then upgrade to TF 1.2.
* TensorForest Estimator now supports SavedModel export for serving.
* Support client-provided ClusterSpec's and propagate them to all workers to enable the creation of dynamic TensorFlow clusters.
* TensorFlow C library now available for Windows.
* We released a new open-source version of TensorBoard.

## Breaking Changes to the API
* org.tensorflow.contrib.android.TensorFLowInferenceInterface now throws exceptions where possible and and has simplified method signatures.

## Changes to contrib APIs
* Added `tf.contrib.util.create_example`.
* Added bilinear interpolation to tf.contrib.image.
* Add `tf.contrib.stateless` for random ops with custom seed control.
* Add ScaM op to contrib for fast approximate nearest neighbor computation.
* MultivariateNormalFullCovariance added to contrib/distributions/

## Bug Fixes and Other Changes
* In python, `Operation.get_attr` on type attributes returns the Python DType
  version of the type to match expected get_attr documentation rather than the
  protobuf enum.
* Changed MIN_SDK version to 8.0 when building iOS libraries.
* Fixed LIBXSMM integration.
* Make decode_jpeg/decode_png/decode_gif handle all formats, since users frequently try to decode an image as the wrong type.
* Improve implicit broadcasting lowering.
* Improving stability of GCS/Bigquery clients by a faster retrying of stale transmissions.
* Remove OpKernelConstruction::op_def() as part of minimizing proto dependencies.
* VectorLaplaceDiag distribution added.
* Android demo no longer requires libtensorflow_demo.so to run (libtensorflow_inference.so still required)
* Added `categorical_column_with_vocabulary_file`.
* Introduce ops for batching/unbatching tensors across Session::Run() calls.
* Add tf.log_sigmoid(x) = tf.log(tf.sigmoid(x)) = -tf.nn.softplus(-x).
* Changed hooks lists to immutable tuples, and now allow any iterable for the associated arguments.
* Introduce TFDecorator.
* Added an Mfcc op for speech feature generation.
* Improved DirectSession::Run() overhead and error checking. Feeding a value of the wrong type will now synchronously raise an INVALID_ARGUMENT error instead of asynchronously raising an INTERNAL error. Code that depends on the (undefined) behavior when feeding a tensor of the wrong type may need to be updated.
* Added unreduced NONE, and reduced MEAN options for losses. Removed "WEIGHTED_" prefix from other Reduction constants.
* assertAllClose now handles dicts.
* Added Gmock matcher for HloInstructions.
* Add var name to errors on variable restore.
* Added an AudioSpectrogram op for audio feature generation.
* Added `reduction` arg to losses.
* `tf.placeholder` can represent scalar shapes and partially known.
* Remove estimator_spec(mode) argument.
* Added an AudioSpectrogram op for audio feature generation.
* TensorBoard disables all runs by default if there are more than 40 runs.
* Removed old doc generator code.
* GCS file system integration now supports domain buckets, e.g gs://bucket.domain.com/path.
* Add `tf.summary.text` for outputting text to TensorBoard.
* The "run" command of tfdbg's command-line interface now supports filtering of tensors by node name, op type and tensor dtype.
* `tf.string_to_number` now supports int64 and float64 outputs.
* `SavedModel CLI` tool available to inspect and execute MetaGraph in SavedModel

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as:

4F2E4A2E, Aaron Schumacher, Abhi Agg, admcrae, Adriano Carmezim, Adrià Arrufat,
agramesh1, Akimitsu Seo, Alan Mosca, Alex Egg, Alex Rothberg, Alexander Heinecke,
Alexander Matyasko, Alexandr Baranezky, Alexandre Caulier, Ali Siddiqui, Anand Venkat,
Andrew Hundt, Androbin, Anmol Sharma, Arie, Arno Leist, Arron Cao, AuréLien Geron, Bairen Yi,
Beomsu Kim, Carl Thomé, cfperez, Changming Sun, Corey Wharton, critiqjo, Dalei Li, Daniel
Rasmussen, Daniel Trebbien, DaríO Hereñú, David Eng, David Norman, David Y. Zhang, Davy Song, ddurham2,
Deepak Subburam, Dmytro Kyrychuk, Dominic Rossi, Dominik SchlöSser, Dustin Tran,
Eduardo Pinho, Egil Martinsson, Elliot Saba, Eric Bigelow, Erik Smistad, Evan Klitzke,
Fabrizio Milo, Falcon Dai, Fei Gao, FloopCZ, Fung Lam, Gautam, GBLin5566, Greg Peatfield,
Gu Wang, Guenther Schmuelling, Hans Pabst, Harun Gunaydin, Huaizheng, Ido Shamay, Ikaro
Silva, Ilya Edrenkin, Immexxx, James Mishra, Jamie Cooke, Jay Young, Jayaram Bobba,
Jianfei Wang, jinghua2, Joey Meyer, John Maidens, Jonghoon Jin, Julian Villella,
Jun Kim, Jun Shi, Junwei Pan, jyegerlehner, Karan Desai, Karel Van De Plassche,
Kb Sriram, KhabarlakKonstantin, Koan-Sin Tan, krivard, Kwotsin, Leandro Gracia Gil,
Li Chen, Liangliang He, Louie Helm, lspvic, Luiz Henrique Soares, LáSzló Csomor,
Mark Wong, Mathew Wicks, Matthew Rahtz, Maxwell Paul Brickner, Michael Hofmann, Miguel
Flores Ruiz De Eguino, MikeTam1021, Mortada Mehyar, Mycosynth, Namnamseo,
Nate Harada, Neven Miculinic, Nghia Tran, Nick Lyu, Niranjan Hasabnis, Nishidha, Oleksii
Kuchaiev, Oyesh Mann Singh, Panmari, Patrick, Paul Van Eck, Piyush Chaudhary, Quim Llimona,
Raingo, Richard Davies, Ruben Vereecken, Sahit Chintalapudi, Sam Abrahams, Santiago Castro,
Scott Sievert, Sean O'Keefe, Sebastian Schlecht, Shane, Shubhankar Deshpande, Spencer Schaber,
Sunyeop Lee, t13m, td2014, Thomas H. P. Andersen, Toby Petty, Umang Mehta,
Vadim Markovtsev, Valentin Iovene, Vincent Zhao, Vit Stepanovs, Vivek Rane, Vu Pham, wannabesrevenge,
weipingpku, wuhaixutab, wydwww, Xiang Gao, Xiaolin Lin, xiaoyaozhuzi, Yaroslav Bulatov, Yi Liu,
Yoshihiro Sugi, Yuan (Terry) Tang, Yuming Wang, Yuxin Wu, Zader Zheng, Zhaojun Zhang, zhengjiajin,
ZhipengShen, Ziming Dong, zjj2wry

We are also grateful to all who filed issues or helped resolve them, asked and
answered questions, and were part of inspiring discussions.

Tensorflow Lite楽しんで待ってます。笑

# Tesorflow Lite 参考ニュース

1. [Google’s TensorFlow Lite brings machine learning to Android devices](https://techcrunch.com/2017/05/17/googles-tensorflow-lite-brings-machine-learning-to-android-devices/)
2. [Google Launches TensorFlow Lite for Mobile Machine Learning](https://www.xda-developers.com/tensorflow-lite-mobile-machine-learning/)
3. [https://venturebeat.com/2017/05/17/android-launches-tensorflow-lite-for-mobile-machine-learning/](https://venturebeat.com/2017/05/17/android-launches-tensorflow-lite-for-mobile-machine-learning/)

す。。。すごい。。です。

![google lens.gif](https://qiita-image-store.s3.amazonaws.com/0/137182/00007324-eed1-565c-0ce8-a2fb509391cb.gif)