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rapidrabbit76 / PaintsTensorFlow

line drawing colorization using TensorFlow
MIT License
52 stars 6 forks source link

Bump tensorflow from 1.12.2 to 1.15.4 #10

Closed dependabot[bot] closed 4 years ago

dependabot[bot] commented 4 years ago

Bumps tensorflow from 1.12.2 to 1.15.4.

Release notes

Sourced from tensorflow'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'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[bot] commented 4 years ago

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.