MrGiovanni / UNetPlusPlus

[IEEE TMI] Official Implementation for UNet++
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Bump tensorflow-gpu from 1.4.1 to 1.15.4 in /keras #58

Closed dependabot[bot] closed 3 years ago

dependabot[bot] commented 3 years ago

Bumps tensorflow-gpu from 1.4.1 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

... (truncated)

Commits
  • d0dbdb7 Support py_func op in TFRT.
  • aab9c69 Fix Windows build.
  • 4cd80bd [tf.data] Turn off the experiment enable_gradient_descent currently.
  • 8f56cdc Fixes an issue where aar_with_jni fails when building with --config=android_j...
  • c11d0de Internal change: Remove tensor_shape.as_dimension from Keras.
  • 2889cec Add output_shapes attribute to tf.WhileRegion.
  • c77657c [XLA:GPU] Add unit test to test PadToStatic IR emission
  • 6a83a28 Link to the bug where we change the inter_op pool size in in-process cluster.
  • f473a44 Update sidecar_evaluator to use tf.logging instead of absl logging.
  • 39aa67d Some internal change
  • Additional commits viewable in compare view


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dependabot[bot] commented 3 years ago

Superseded by #59.