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TensorFlow 1.7.0

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@annarev annarev released this 29 Mar 20:29
· 42 commits to r1.7 since this release
v1.7.0
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Release 1.7.0

Major Features And Improvements

  • Eager mode is moving out of contrib, try tf.enable_eager_execution().
  • Graph rewrites emulating fixed-point quantization compatible with TensorFlow Lite, supported by new tf.contrib.quantize package.
  • Easily customize gradient computation with tf.custom_gradient.
  • TensorBoard Debugger Plugin, the graphical user interface (GUI) of TensorFlow Debugger (tfdbg), is now in alpha.
  • Experimental support for reading a sqlite database as a Dataset with new tf.contrib.data.SqlDataset.
  • Distributed Mutex / CriticalSection added to tf.contrib.framework.CriticalSection.
  • Better text processing with tf.regex_replace.
  • Easy, efficient sequence input with tf.contrib.data.bucket_by_sequence_length
  • Initial support for tf.contrib.tensorrt that enables native TensorRT in TensorFlow

Bug Fixes and Other Changes

  • Accelerated Linear Algebra (XLA):
    • Add MaxPoolGradGrad support for XLA
    • CSE pass from Tensorflow is now disabled in XLA.
  • tf.data:
    • tf.data.Dataset
      • Add support for building C++ Dataset op kernels as external libraries, using the tf.load_op_library() mechanism.
      • Dataset.list_files() now shuffles its output by default.
      • Dataset.shuffle(..., seed=tf.constant(0, dtype=tf.int64)) now yields the same sequence of elements as Dataset.shuffle(..., seed=0).
    • Add num_parallel_reads argument to tf.data.TFRecordDataset.
  • tf.contrib:
    • tf.contrib.bayesflow.halton_sequence now supports randomization.
    • Add support for scalars in tf.contrib.all_reduce.
    • Add effective_sample_size to tf.contrib.bayesflow.mcmc_diagnostics.
    • Add potential_scale_reduction to tf.contrib.bayesflow.mcmc_diagnostics.
    • Add BatchNormalization, Kumaraswamy bijectors.
    • Deprecate tf.contrib.learn. Please check contrib/learn/README.md for instructions on how to convert existing code.
    • tf.contrib.data
      • Remove deprecated tf.contrib.data.Dataset, tf.contrib.data.Iterator, tf.contrib.data.FixedLengthRecordDataset, tf.contrib.data.TextLineDataset, and tf.contrib.data.TFRecordDataset classes.
      • Added bucket_by_sequence_length, sliding_window_batch, and make_batched_features_dataset
    • Remove unmaintained tf.contrib.ndlstm. You can find it externally at https://github.com/tmbarchive/tfndlstm.
    • Moved most of tf.contrib.bayesflow to its own repo: tfp
  • Other:
    • tf.py_func now reports the full stack trace if an exception occurs.
    • Integrate TPUClusterResolver with GKE's integration for Cloud TPUs.
    • Add a library for statistical testing of samplers.
    • Add Helpers to stream data from the GCE VM to a Cloud TPU.
    • Integrate ClusterResolvers with TPUEstimator.
    • Unify metropolis_hastings interface with HMC kernel.
    • Move LIBXSMM convolutions to a separate --define flag so that they are disabled by default.
    • Fix MomentumOptimizer lambda.
    • Reduce tfp.layers boilerplate via programmable docstrings.
    • Add auc_with_confidence_intervals, a method for computing the AUC and confidence interval with linearithmic time complexity.
    • regression_head now accepts customized link function, to satisfy the usage that user can define their own link function if the array_ops.identity does not meet the requirement.
    • Fix initialized_value and initial_value behaviors for ResourceVariables created from VariableDef protos.
    • Add TensorSpec to represent the specification of Tensors.
    • Constant folding pass is now deterministic.
    • Support float16 dtype in tf.linalg.*.
    • Add tf.estimator.export.TensorServingInputReceiver that allows tf.estimator.Estimator.export_savedmodel to pass raw tensors to model functions.

Deprecations

  • TensorFlow 1.7 may be the last time we support Cuda versions below 8.0.
    Starting with TensorFlow 1.8 release, 8.0 will be the minimum supported
    version.
  • TensorFlow 1.7 may be the last time we support cuDNN versions below 6.0.
    Starting with TensorFlow 1.8 release, 6.0 will be the minimum supported
    version.

Thanks to our Contributors

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

4d55397500, Abe, Alistair Low, Andy Kernahan, Appledore, Ben, Ben Barsdell, Boris Pfahringer, Brad Wannow, Brett Koonce, Carl Thomé, cclauss, Chengzhi Chen, Chris Drake, Christopher Yeh, Clayne Robison, Codrut Grosu, Daniel Trebbien, Danny Goodman, David Goodwin, David Norman, Deron Eriksson, Donggeon Lim, Donny Viszneki, DosLin, DylanDmitri, Francisco Guerrero, Fred Reiss, gdh1995, Giuseppe, Glenn Weidner, gracehoney, Guozhong Zhuang, Haichen "Hc" Li, Harald Husum, harumitsu.nobuta, Henry Spivey, hsm207, Jekyll Song, Jerome, Jiongyan Zhang, jjsjann123, John Sungjin Park, Johnson145, JoshVarty, Julian Wolff, Jun Wang, June-One, Kamil Sindi, Kb Sriram, Kdavis-Mozilla, Kenji, lazypanda1, Liang-Chi Hsieh, Loo Rong Jie, Mahesh Bhosale, MandarJKulkarni, ManHyuk, Marcus Ong, Marshal Hayes, Martin Pool, matthieudelaro, mdfaijul, mholzel, Michael Zhou, Ming Li, Minmin Sun, Myungjoo Ham, MyungsungKwak, Naman Kamra, Peng Yu, Penghao Cen, Phil, Raghuraman-K, resec, Rohin Mohanadas, Sandeep N Gupta, Scott Tseng, seaotterman, Seo Sanghyeon, Sergei Lebedev, Ted Chang, Tim H, tkunic, Tod, vihanjain, Yan Facai (颜发才), Yin Li, Yong Tang, Yuan (Terry) Tang, Yukun Chen, Yusuke Yamada

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