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Bump tensorflow from 1.4.1 to 1.12.2 in /darkflow/test - #5

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Bump tensorflow from 1.4.1 to 1.12.2 in /darkflow/test#5
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@dependabotdependabotBot commented on behalf of githubSep 30, 2019

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Bumps tensorflow from 1.4.1 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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@dependabotdependabotBot added the dependencies Pull requests that update a dependency file label Sep 30, 2019
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dependabotBot commented on behalf of githubDec 16, 2019

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Superseded by #7.

@dependabotdependabotBot closed this Dec 16, 2019
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dependabotBot deleted the dependabot/pip/darkflow/test/tensorflow-1.12.2 branch December 16, 2019 22:14
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