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Bump tensorflow from 1.0 to 2.9.3 in /OpenSourceProjects/Deep-Learning-21-Examples-master/chapter_6 #76

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@dependabot dependabot bot commented on behalf of github Nov 21, 2022

Bumps tensorflow from 1.0 to 2.9.3.

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.9.3

Release 2.9.3

This release introduces several vulnerability fixes:

TensorFlow 2.9.2

Release 2.9.2

This releases introduces several vulnerability fixes:

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.11.0

Breaking Changes

  • tf.keras.optimizers.Optimizer now points to the new Keras optimizer, and old optimizers have moved to the tf.keras.optimizers.legacy namespace. If you find your workflow failing due to this change, you may be facing one of the following issues:

    • Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to tf.keras.optimizers.legacy.XXX (e.g. tf.keras.optimizers.legacy.Adam).
    • TF1 compatibility. The new optimizer does not support TF1 any more, so please use the legacy optimizer tf.keras.optimizer.legacy.XXX. We highly recommend to migrate your workflow to TF2 for stable support and new features.
    • API not found. The new optimizer has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API documentation to find alternatives to the missing API. If you must call the deprecated API, please change your optimizer to the legacy optimizer.
    • Learning rate schedule access. When using a LearningRateSchedule, The new optimizer's learning_rate property returns the current learning rate value instead of a LearningRateSchedule object as before. If you need to access the LearningRateSchedule object, please use optimizer._learning_rate.
    • You implemented a custom optimizer based on the old optimizer. Please set your optimizer to subclass tf.keras.optimizer.legacy.XXX. If you want to migrate to the new optimizer and find it does not support your optimizer, please file an issue in the Keras GitHub repo.
    • Error such as Cannot recognize variable.... The new optimizer requires all optimizer variables to be created at the first apply_gradients() or minimize() call. If your workflow calls optimizer to update different parts of model in multiple stages, please call optimizer.build(model.trainable_variables) before the training loop.
    • Performance regression on ParameterServerStrategy. This could be significant if you have many PS servers. We are aware of this issue and working on fixes, for now we suggest using the legacy optimizers when using ParameterServerStrategy.
    • Timeout or performance loss. We don't anticipate this to happen, but if you see such issues, please use the legacy optimizer, and file an issue in the Keras GitHub repo.

    The old Keras optimizer will never be deleted, but will not see any

... (truncated)

Commits
  • a5ed5f3 Merge pull request #58584 from tensorflow/vinila21-patch-2
  • 258f9a1 Update py_func.cc
  • cd27cfb Merge pull request #58580 from tensorflow-jenkins/version-numbers-2.9.3-24474
  • 3e75385 Update version numbers to 2.9.3
  • bc72c39 Merge pull request #58482 from tensorflow-jenkins/relnotes-2.9.3-25695
  • 3506c90 Update RELEASE.md
  • 8dcb48e Update RELEASE.md
  • 4f34ec8 Merge pull request #58576 from pak-laura/c2.99f03a9d3bafe902c1e6beb105b2f2417...
  • 6fc67e4 Replace CHECK with returning an InternalError on failing to create python tuple
  • 5dbe90a Merge pull request #58570 from tensorflow/r2.9-7b174a0f2e4
  • Additional commits viewable in compare view

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Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 1.0 to 2.9.3.
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v1.0.0...v2.9.3)

---
updated-dependencies:
- dependency-name: tensorflow
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
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