sermakarevich / jigsaw-toxic-comment-classification-challenge

46 stars 8 forks source link

Bump tensorflow from 1.12.2 to 2.3.1 #16

Closed dependabot[bot] closed 3 years ago

dependabot[bot] commented 3 years ago

Bumps tensorflow from 1.12.2 to 2.3.1.

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.3.1

Release 2.3.1

Bug Fixes and Other Changes

TensorFlow 2.3.0

Release 2.3.0

Major Features and Improvements

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

In addition checkout the detailed guide for analyzing input pipeline performance with TF Profiler.

  • tf.distribute.TPUStrategy is now a stable API and no longer considered experimental for TensorFlow. (earlier tf.distribute.experimental.TPUStrategy).

  • TF Profiler introduces two new tools: a memory profiler to visualize your model’s memory usage over time and a python tracer which allows you to trace python function calls in your model. Usability improvements include better diagnostic messages and profile options to customize the host and device trace verbosity level.

  • Introduces experimental support for Keras Preprocessing Layers API (tf.keras.layers.experimental.preprocessing.*) to handle data preprocessing operations, with support for composite tensor inputs. Please see below for additional details on these layers.

  • TFLite now properly supports dynamic shapes during conversion and inference. We’ve also added opt-in support on Android and iOS for XNNPACK, a highly optimized set of CPU kernels, as well as opt-in support for executing quantized models on the GPU.

  • Libtensorflow packages are available in GCS starting this release. We have also started to release a nightly version of these packages.

  • The experimental Python API tf.debugging.experimental.enable_dump_debug_info() now allows you to instrument a TensorFlow program and dump debugging information to a directory on the file system. The directory can be read and visualized by a new interactive dashboard in TensorBoard 2.3 called Debugger V2, which reveals the details of the TensorFlow program including graph structures, history of op executions at the Python (eager) and intra-graph levels, the runtime dtype, shape, and numerical composistion of tensors, as well as their code locations.

Breaking Changes

  • Increases the minimum bazel version required to build TF to 3.1.0.
  • tf.data
    • Makes the following (breaking) changes to the tf.data.
    • C++ API: - IteratorBase::RestoreInternal, IteratorBase::SaveInternal, and DatasetBase::CheckExternalState become pure-virtual and subclasses are now expected to provide an implementation.
    • The deprecated DatasetBase::IsStateful method is removed in favor of DatasetBase::CheckExternalState.
    • Deprecated overrides of DatasetBase::MakeIterator and MakeIteratorFromInputElement are removed.

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.3.1

Bug Fixes and Other Changes

Release 2.2.1

... (truncated)

Commits
  • fcc4b96 Merge pull request #43446 from tensorflow-jenkins/version-numbers-2.3.1-16251
  • 4cf2230 Update version numbers to 2.3.1
  • eee8224 Merge pull request #43441 from tensorflow-jenkins/relnotes-2.3.1-24672
  • 0d41b1d Update RELEASE.md
  • d99bd63 Insert release notes place-fill
  • d71d3ce Merge pull request #43414 from tensorflow/mihaimaruseac-patch-1-1
  • 9c91596 Fix missing import
  • f9f12f6 Merge pull request #43391 from tensorflow/mihaimaruseac-patch-4
  • 3ed271b Solve leftover from merge conflict
  • 9cf3773 Merge pull request #43358 from tensorflow/mm-patch-r2.3
  • Additional commits viewable in compare view


Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/sermakarevich/jigsaw-toxic-comment-classification-challenge/network/alerts).
dependabot[bot] commented 3 years ago

Superseded by #22.