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Bump tensorflow from 1.1.0 to 1.12.2 #93

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merged 3 commits into from
Jul 16, 2019

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@dependabot dependabot bot commented on behalf of github Jun 28, 2019

Bumps tensorflow from 1.1.0 to 1.12.2.

Release notes

Sourced from tensorflow's releases.

TensorFlow 1.12.2

Release 1.12.2

Bug Fixes and Other Changes

  • Fixes a potential security vulnerability where carefully crafted GIF images can produce a null pointer dereference during decoding

TensorFlow 1.12.0

Release 1.12.0

Major Features and Improvements

  • Keras models can now be directly exported to the SavedModel format(tf.contrib.saved_model.save_keras_model()) and used with Tensorflow Serving.
  • Keras models now support evaluating with a tf.data.Dataset.
  • TensorFlow binaries are built with XLA support linked in by default.
  • Ignite Dataset added to contrib/ignite that allows to work with Apache Ignite.

Bug Fixes and Other Changes

  • tf.data:
    • tf.data users can now represent, get, and set options of TensorFlow input pipelines using tf.data.Options(), tf.data.Dataset.options(), and tf.data.Dataset.with_options() respectively.
    • New tf.data.Dataset.reduce() API allows users to reduce a finite dataset to a single element using a user-provided reduce function.
    • New tf.data.Dataset.window() API allows users to create finite windows of input dataset; when combined with the tf.data.Dataset.reduce() API, this allows users to implement customized batching.
    • All C++ code moves to the tensorflow::data namespace.
    • Add support for num_parallel_calls to tf.data.Dataset.interleave.
  • tf.contrib:
    • Remove tf.contrib.linalg. tf.linalg should be used instead.
    • Replace any calls to tf.contrib.get_signature_def_by_key(metagraph_def, signature_def_key) with meta_graph_def.signature_def[signature_def_key]. Catching a ValueError exception thrown by tf.contrib.get_signature_def_by_key should be replaced by catching a KeyError exception.
  • tf.contrib.data
    • Deprecate, and replace by tf.data.experimental.
  • Other:
    • Improved XLA stability and performance.
    • Fix single replica TensorBoard summary stats in Cloud ML Engine.
    • TPUEstimator: Initialize dataset iterators in parallel.
    • Keras on TPU model quality and bug fixes.
    • Instead of jemalloc, revert back to using system malloc since it simplifies build and has comparable performance.
    • Remove integer types from tf.nn.softplus and tf.nn.softsign OpDefs. This is a bugfix; these ops were never meant to support integers.
    • Allow subslicing Tensors with a single dimension.
    • Add option to calculate string length in Unicode characters
    • Add functionality to SubSlice a tensor.
    • Add searchsorted (ie lower/upper_bound) op.
    • Add model explainability to Boosted Trees.
    • Support negative positions for tf.substr
    • There was previously a bug in the bijector_impl where the _reduce_jacobian_det_over_event does not handle scalar ILDJ implementations properly.
    • In tf eager execution, allow re-entering a GradientTape context
    • Add tf_api_version flag. If --define=tf_api_version=2 flag is passed in, then bazel will build TensorFlow API version 2.0. Note that TensorFlow 2.0 is under active development and has no guarantees at this point.
    • Add additional compression options to TfRecordWriter
    • Performance improvements for regex full match operations.
    • Replace tf.GraphKeys.VARIABLES with tf.GraphKeys.GLOBAL_VARIABLES
    • Remove unused dynamic learning rate support.

Thanks to our Contributors

... (truncated)
Changelog

Sourced from tensorflow's changelog.

Release 1.12.2

Bug Fixes and Other Changes

  • Fixes a potential security vulnerability where carefully crafted GIF images
    can produce a null pointer dereference during decoding.

Release 1.13.0

Major Features and Improvements

  • TensorFlow Lite has moved from contrib to core. This means that Python modules are under tf.lite and source code is now under tensorflow/lite rather than tensorflow/contrib/lite.
  • TensorFlow GPU binaries are now built against CUDA 10 and TensorRT 5.0.
  • Support for Python3.7 on all operating systems.
  • Moved NCCL to core.

Behavioral changes

  • Disallow conversion of python floating types to uint32/64 (matching behavior of other integer types) in tf.constant.
  • Make the gain argument of convolutional orthogonal initializers (convolutional_delta_orthogonal, convolutional_orthogonal_1D, convolutional_orthogonal_2D, convolutional_orthogonal_3D) have consistent behavior with the tf.initializers.orthogonal initializer, i.e. scale the output l2-norm by gain and NOT by sqrt(gain). (Note that these functions are currently in tf.contrib which is not guaranteed backward compatible).

Bug Fixes and Other Changes

  • Documentation
    • Update the doc with the details about the rounding mode used in
      quantize_and_dequantize_v2.
    • Clarify that tensorflow::port::InitMain() should be called before
      using the TensorFlow library. Programs failing to do this are not
      portable to all platforms.
  • Deprecations and Symbol renames.
    • Removing deprecations for the following endpoints: tf.acos,
      tf.acosh, tf.add, tf.as_string, tf.asin, tf.asinh, tf.atan,
      tf.atan2, tf.atanh, tf.cos, tf.cosh, tf.equal, tf.exp,
      tf.floor, tf.greater, tf.greater_equal, tf.less,
      tf.less_equal, tf.log, tf.logp1, tf.logical_and,
      tf.logical_not, tf.logical_or, tf.maximum, tf.minimum,
      tf.not_equal, tf.sin, tf.sinh, tf.tan
    • Deprecate tf.data.Dataset.shard.
    • Deprecate saved_model.loader.load which is replaced by
      saved_model.load and saved_model.main_op, which will be replaced by
      saved_model.main_op in V2.
    • Deprecate tf.QUANTIZED_DTYPES. The official new symbol is
      tf.dtypes.QUANTIZED_DTYPES.
    • Update sklearn imports for deprecated packages.
    • Deprecate Variable.count_up_to and tf.count_up_to in favor of
      Dataset.range.
    • Export confusion_matrix op as tf.math.confusion_matrix instead of
      tf.train.confusion_matrix.
    • Add tf.dtypes. endpoint for every constant in dtypes.py. Moving
      endpoints in versions.py to corresponding endpoints in tf.sysconfig.
... (truncated)
Commits
  • 6b63465 Merge pull request #27959 from tensorflow/update-release-notes-version
  • e967833 Update header on release notes
  • cf74798 Merge pull request #27958 from tensorflow/update-release-version
  • 7fba173 Update version to 1.12.2
  • 332f080 Merge pull request #27878 from tensorflow/windows-cpu
  • c9fcc49 Fix windows build for CPU too
  • 416b4a3 Merge pull request #27873 from tensorflow/more-bazel-incompatible-flags
  • 3ebe165 Add --incompatible_disable_cc_toolchain_label_from_crosstool_proto=false flag
  • 5ab9466 Reformat bazel invocation lines
  • 446d393 Merge pull request #27870 from tensorflow/bazel-http-archive
  • Additional commits viewable in compare view

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Jun 28, 2019
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/lgtm
@hoffmansc any comments?

@dependabot dependabot bot force-pushed the dependabot/pip/tensorflow-1.12.2 branch from eca382d to 23c7935 Compare July 9, 2019 13:51
@hoffmansc hoffmansc merged commit ec6fa98 into master Jul 16, 2019
@hoffmansc hoffmansc deleted the dependabot/pip/tensorflow-1.12.2 branch July 16, 2019 02:48
Illia-Kryvoviaz pushed a commit to Illia-Kryvoviaz/AIF360 that referenced this pull request Jun 7, 2023
security patch for tensorflow; took this opportunity to support Python 3.7 and update readme instructions
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