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Bump tensorflow-gpu from 1.14.0 to 1.15.4 in /python #5

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@dependabot dependabot bot commented on behalf of github Sep 25, 2020

Bumps tensorflow-gpu from 1.14.0 to 1.15.4.

Release notes

Sourced from tensorflow-gpu's releases.

TensorFlow 1.15.4

Release 1.15.4

Bug Fixes and Other Changes

TensorFlow 1.15.3

Bug Fixes and Other Changes

TensorFlow 1.15.2

Release 1.15.2

Note that this release no longer has a single pip package for GPU and CPU. Please see #36347 for history and details

Bug Fixes and Other Changes

TensorFlow 1.15.0

Release 1.15.0

This is the last 1.x release for TensorFlow. We do not expect to update the 1.x branch with features, although we will issue patch releases to fix vulnerabilities for at least one year.

Major Features and Improvements

  • As announced, tensorflow pip package will by default include GPU support (same as tensorflow-gpu now) for the platforms we currently have GPU support (Linux and Windows). It will work on machines with and without Nvidia GPUs. tensorflow-gpu will still be available, and CPU-only packages can be downloaded at tensorflow-cpu for users who are concerned about package size.
  • TensorFlow 1.15 contains a complete implementation of the 2.0 API in its compat.v2 module. It contains a copy of the 1.15 main module (without contrib) in the compat.v1 module. TensorFlow 1.15 is able to emulate 2.0 behavior using the enable_v2_behavior() function. This enables writing forward compatible code: by explicitly importing either tensorflow.compat.v1 or tensorflow.compat.v2, you can ensure that your code works without modifications against an installation of 1.15 or 2.0.
  • EagerTensor now supports numpy buffer interface for tensors.
  • Add toggles tf.enable_control_flow_v2() and tf.disable_control_flow_v2() for enabling/disabling v2 control flow.
  • Enable v2 control flow as part of tf.enable_v2_behavior() and TF2_BEHAVIOR=1.
  • AutoGraph translates Python control flow into TensorFlow expressions, allowing users to write regular Python inside tf.function-decorated functions. AutoGraph is also applied in functions used with tf.data, tf.distribute and tf.keras APIS.
  • Adds enable_tensor_equality(), which switches the behavior such that:
    • Tensors are no longer hashable.

... (truncated)

Changelog

Sourced from tensorflow-gpu's changelog.

Release 1.15.4

Bug Fixes and Other Changes

Release 2.3.0

Major Features and Improvements

  • tf.data adds two new mechanisms to solve input pipeline bottlenecks and save resources:

... (truncated)

Commits
  • df8c55c Merge pull request #43442 from tensorflow-jenkins/version-numbers-1.15.4-31571
  • 0e8cbcb Update version numbers to 1.15.4
  • 5b65bf2 Merge pull request #43437 from tensorflow-jenkins/relnotes-1.15.4-10691
  • 814e8d8 Update RELEASE.md
  • 757085e Insert release notes place-fill
  • e99e53d Merge pull request #43410 from tensorflow/mm-fix-1.15
  • bad36df Add missing import
  • f3f1835 No disable_tfrt present on this branch
  • 7ef5c62 Merge pull request #43406 from tensorflow/mihaimaruseac-patch-1
  • abbf34a Remove import that is not needed
  • Additional commits viewable in compare view

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Sep 25, 2020
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dependabot bot commented on behalf of github Sep 28, 2020

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

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dependabot bot commented on behalf of github Sep 28, 2020

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

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