Release notes
*Sourced from [tensorflow's releases](https://github.com/tensorflow/tensorflow/releases).*
> ## TensorFlow 1.12.2
> # Release 1.12.2
> ## Bug Fixes and Other Changes
>
> * Fixes a potential security vulnerability where carefully crafted GIF images can produce a null pointer dereference during decoding
>
> ## TensorFlow 1.12.0
> # Release 1.12.0
>
> ## Major Features and Improvements
> * Keras models can now be directly exported to the SavedModel format(`tf.contrib.saved_model.save_keras_model()`) and used with Tensorflow Serving.
> * Keras models now support evaluating with a `tf.data.Dataset`.
> * TensorFlow binaries are built with XLA support linked in by default.
> * Ignite Dataset added to contrib/ignite that allows to work with Apache Ignite.
>
> ## Bug Fixes and Other Changes
>
> * `tf.data`:
> * `tf.data` users can now represent, get, and set options of TensorFlow input pipelines using `tf.data.Options()`, `tf.data.Dataset.options()`, and `tf.data.Dataset.with_options()` respectively.
> * New `tf.data.Dataset.reduce()` API allows users to reduce a finite dataset to a single element using a user-provided reduce function.
> * New `tf.data.Dataset.window()` API allows users to create finite windows of input dataset; when combined with the `tf.data.Dataset.reduce()` API, this allows users to implement customized batching.
> * All C++ code moves to the `tensorflow::data` namespace.
> * Add support for `num_parallel_calls` to `tf.data.Dataset.interleave`.
> * `tf.contrib`:
> * Remove `tf.contrib.linalg`. `tf.linalg` should be used instead.
> * Replace any calls to `tf.contrib.get_signature_def_by_key(metagraph_def, signature_def_key)` with `meta_graph_def.signature_def[signature_def_key]`. Catching a ValueError exception thrown by `tf.contrib.get_signature_def_by_key` should be replaced by catching a KeyError exception.
> * `tf.contrib.data`
> * Deprecate, and replace by tf.data.experimental.
> * Other:
> * Improved XLA stability and performance.
> * Fix single replica TensorBoard summary stats in Cloud ML Engine.
> * TPUEstimator: Initialize dataset iterators in parallel.
> * Keras on TPU model quality and bug fixes.
> * Instead of jemalloc, revert back to using system malloc since it simplifies build and has comparable performance.
> * Remove integer types from `tf.nn.softplus` and `tf.nn.softsign` OpDefs. This is a bugfix; these ops were never meant to support integers.
> * Allow subslicing Tensors with a single dimension.
> * Add option to calculate string length in Unicode characters
> * Add functionality to SubSlice a tensor.
> * Add searchsorted (ie lower/upper_bound) op.
> * Add model explainability to Boosted Trees.
> * Support negative positions for tf.substr
> * There was previously a bug in the bijector_impl where the _reduce_jacobian_det_over_event does not handle scalar ILDJ implementations properly.
> * In tf eager execution, allow re-entering a GradientTape context
> * Add tf_api_version flag. If --define=tf_api_version=2 flag is passed in, then bazel will build TensorFlow API version 2.0. Note that TensorFlow 2.0 is under active development and has no guarantees at this point.
> * Add additional compression options to TfRecordWriter
> * Performance improvements for regex full match operations.
> * Replace `tf.GraphKeys.VARIABLES` with `tf.GraphKeys.GLOBAL_VARIABLES`
> * Remove unused dynamic learning rate support.
>
> ## Thanks to our Contributors
> ... (truncated)
Changelog
*Sourced from [tensorflow's changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md).*
> # Release 1.12.2
>
> ## Bug Fixes and Other Changes
>
> * Fixes a potential security vulnerability where carefully crafted GIF images
> can produce a null pointer dereference during decoding.
>
> # Release 1.13.0
>
> ## Major Features and Improvements
>
> * TensorFlow Lite has moved from contrib to core. This means that Python modules are under `tf.lite` and source code is now under `tensorflow/lite` rather than `tensorflow/contrib/lite`.
> * TensorFlow GPU binaries are now built against CUDA 10 and TensorRT 5.0.
> * Support for Python3.7 on all operating systems.
> * Moved NCCL to core.
>
> ## Behavioral changes
>
> * Disallow conversion of python floating types to uint32/64 (matching behavior of other integer types) in `tf.constant`.
> * Make the `gain` argument of convolutional orthogonal initializers (`convolutional_delta_orthogonal`, `convolutional_orthogonal_1D`, `convolutional_orthogonal_2D`, `convolutional_orthogonal_3D`) have consistent behavior with the `tf.initializers.orthogonal` initializer, i.e. scale the output l2-norm by `gain` and NOT by `sqrt(gain)`. (Note that these functions are currently in `tf.contrib` which is not guaranteed backward compatible).
>
> ## Bug Fixes and Other Changes
>
> * Documentation
> * Update the doc with the details about the rounding mode used in
> quantize_and_dequantize_v2.
> * Clarify that tensorflow::port::InitMain() _should_ be called before
> using the TensorFlow library. Programs failing to do this are not
> portable to all platforms.
> * Deprecations and Symbol renames.
> * Removing deprecations for the following endpoints: `tf.acos`,
> `tf.acosh`, `tf.add`, `tf.as_string`, `tf.asin`, `tf.asinh`, `tf.atan`,
> `tf.atan2`, `tf.atanh`, `tf.cos`, `tf.cosh`, `tf.equal`, `tf.exp`,
> `tf.floor`, `tf.greater`, `tf.greater_equal`, `tf.less`,
> `tf.less_equal`, `tf.log`, `tf.logp1`, `tf.logical_and`,
> `tf.logical_not`, `tf.logical_or`, `tf.maximum`, `tf.minimum`,
> `tf.not_equal`, `tf.sin`, `tf.sinh`, `tf.tan`
> * Deprecate `tf.data.Dataset.shard`.
> * Deprecate `saved_model.loader.load` which is replaced by
> `saved_model.load` and `saved_model.main_op`, which will be replaced by
> `saved_model.main_op` in V2.
> * Deprecate tf.QUANTIZED_DTYPES. The official new symbol is
> tf.dtypes.QUANTIZED_DTYPES.
> * Update sklearn imports for deprecated packages.
> * Deprecate `Variable.count_up_to` and `tf.count_up_to` in favor of
> `Dataset.range`.
> * Export `confusion_matrix` op as `tf.math.confusion_matrix` instead of
> `tf.train.confusion_matrix`.
> * Add `tf.dtypes.` endpoint for every constant in dtypes.py. Moving
> endpoints in versions.py to corresponding endpoints in `tf.sysconfig.`
> ... (truncated)
Commits
- [`6b63465`](https://github.com/tensorflow/tensorflow/commit/6b634657d8ff1355132c3838271e4f569d1ffaba) Merge pull request [#27959](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27959) from tensorflow/update-release-notes-version
- [`e967833`](https://github.com/tensorflow/tensorflow/commit/e9678339c906d2ffe78a266de23b45348f0087a6) Update header on release notes
- [`cf74798`](https://github.com/tensorflow/tensorflow/commit/cf74798993f545456cb50ec188f4e25e4b4514c1) Merge pull request [#27958](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27958) from tensorflow/update-release-version
- [`7fba173`](https://github.com/tensorflow/tensorflow/commit/7fba173bcd049c6f6aa871e3ba2e914d38ea20a3) Update version to 1.12.2
- [`332f080`](https://github.com/tensorflow/tensorflow/commit/332f080651162a202069b633d13c6f2e95db63b6) Merge pull request [#27878](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27878) from tensorflow/windows-cpu
- [`c9fcc49`](https://github.com/tensorflow/tensorflow/commit/c9fcc49f5af7ea1985043307a67e8094cde81556) Fix windows build for CPU too
- [`416b4a3`](https://github.com/tensorflow/tensorflow/commit/416b4a3398e814c0abf3101e0d803920852a9bd0) Merge pull request [#27873](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27873) from tensorflow/more-bazel-incompatible-flags
- [`3ebe165`](https://github.com/tensorflow/tensorflow/commit/3ebe165f0bfc62aa0004ffa4d5a15ca4da5029c3) Add --incompatible_disable_cc_toolchain_label_from_crosstool_proto=false flag
- [`5ab9466`](https://github.com/tensorflow/tensorflow/commit/5ab94660a4da3632d5514509d3353d54cbf2e87d) Reformat bazel invocation lines
- [`446d393`](https://github.com/tensorflow/tensorflow/commit/446d3932ffbee93aca87a68427f935d6e598ab14) Merge pull request [#27870](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27870) from tensorflow/bazel-http-archive
- Additional commits viewable in [compare view](https://github.com/tensorflow/tensorflow/compare/v1.11.0...v1.12.2)
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 ignore this [patch|minor|major] version` will close this PR and stop Dependabot creating any more for this minor/major 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/phenompeople/bert-server/network/alerts).
dependabot[bot]
commented
4 years ago
Bumps tensorflow from 1.11.0 to 1.12.2.
Release notes
*Sourced from [tensorflow's releases](https://github.com/tensorflow/tensorflow/releases).* > ## TensorFlow 1.12.2 > # Release 1.12.2 > ## Bug Fixes and Other Changes > > * Fixes a potential security vulnerability where carefully crafted GIF images can produce a null pointer dereference during decoding > > ## TensorFlow 1.12.0 > # Release 1.12.0 > > ## Major Features and Improvements > * Keras models can now be directly exported to the SavedModel format(`tf.contrib.saved_model.save_keras_model()`) and used with Tensorflow Serving. > * Keras models now support evaluating with a `tf.data.Dataset`. > * TensorFlow binaries are built with XLA support linked in by default. > * Ignite Dataset added to contrib/ignite that allows to work with Apache Ignite. > > ## Bug Fixes and Other Changes > > * `tf.data`: > * `tf.data` users can now represent, get, and set options of TensorFlow input pipelines using `tf.data.Options()`, `tf.data.Dataset.options()`, and `tf.data.Dataset.with_options()` respectively. > * New `tf.data.Dataset.reduce()` API allows users to reduce a finite dataset to a single element using a user-provided reduce function. > * New `tf.data.Dataset.window()` API allows users to create finite windows of input dataset; when combined with the `tf.data.Dataset.reduce()` API, this allows users to implement customized batching. > * All C++ code moves to the `tensorflow::data` namespace. > * Add support for `num_parallel_calls` to `tf.data.Dataset.interleave`. > * `tf.contrib`: > * Remove `tf.contrib.linalg`. `tf.linalg` should be used instead. > * Replace any calls to `tf.contrib.get_signature_def_by_key(metagraph_def, signature_def_key)` with `meta_graph_def.signature_def[signature_def_key]`. Catching a ValueError exception thrown by `tf.contrib.get_signature_def_by_key` should be replaced by catching a KeyError exception. > * `tf.contrib.data` > * Deprecate, and replace by tf.data.experimental. > * Other: > * Improved XLA stability and performance. > * Fix single replica TensorBoard summary stats in Cloud ML Engine. > * TPUEstimator: Initialize dataset iterators in parallel. > * Keras on TPU model quality and bug fixes. > * Instead of jemalloc, revert back to using system malloc since it simplifies build and has comparable performance. > * Remove integer types from `tf.nn.softplus` and `tf.nn.softsign` OpDefs. This is a bugfix; these ops were never meant to support integers. > * Allow subslicing Tensors with a single dimension. > * Add option to calculate string length in Unicode characters > * Add functionality to SubSlice a tensor. > * Add searchsorted (ie lower/upper_bound) op. > * Add model explainability to Boosted Trees. > * Support negative positions for tf.substr > * There was previously a bug in the bijector_impl where the _reduce_jacobian_det_over_event does not handle scalar ILDJ implementations properly. > * In tf eager execution, allow re-entering a GradientTape context > * Add tf_api_version flag. If --define=tf_api_version=2 flag is passed in, then bazel will build TensorFlow API version 2.0. Note that TensorFlow 2.0 is under active development and has no guarantees at this point. > * Add additional compression options to TfRecordWriter > * Performance improvements for regex full match operations. > * Replace `tf.GraphKeys.VARIABLES` with `tf.GraphKeys.GLOBAL_VARIABLES` > * Remove unused dynamic learning rate support. > > ## Thanks to our Contributors > ... (truncated)Changelog
*Sourced from [tensorflow's changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md).* > # Release 1.12.2 > > ## Bug Fixes and Other Changes > > * Fixes a potential security vulnerability where carefully crafted GIF images > can produce a null pointer dereference during decoding. > > # Release 1.13.0 > > ## Major Features and Improvements > > * TensorFlow Lite has moved from contrib to core. This means that Python modules are under `tf.lite` and source code is now under `tensorflow/lite` rather than `tensorflow/contrib/lite`. > * TensorFlow GPU binaries are now built against CUDA 10 and TensorRT 5.0. > * Support for Python3.7 on all operating systems. > * Moved NCCL to core. > > ## Behavioral changes > > * Disallow conversion of python floating types to uint32/64 (matching behavior of other integer types) in `tf.constant`. > * Make the `gain` argument of convolutional orthogonal initializers (`convolutional_delta_orthogonal`, `convolutional_orthogonal_1D`, `convolutional_orthogonal_2D`, `convolutional_orthogonal_3D`) have consistent behavior with the `tf.initializers.orthogonal` initializer, i.e. scale the output l2-norm by `gain` and NOT by `sqrt(gain)`. (Note that these functions are currently in `tf.contrib` which is not guaranteed backward compatible). > > ## Bug Fixes and Other Changes > > * Documentation > * Update the doc with the details about the rounding mode used in > quantize_and_dequantize_v2. > * Clarify that tensorflow::port::InitMain() _should_ be called before > using the TensorFlow library. Programs failing to do this are not > portable to all platforms. > * Deprecations and Symbol renames. > * Removing deprecations for the following endpoints: `tf.acos`, > `tf.acosh`, `tf.add`, `tf.as_string`, `tf.asin`, `tf.asinh`, `tf.atan`, > `tf.atan2`, `tf.atanh`, `tf.cos`, `tf.cosh`, `tf.equal`, `tf.exp`, > `tf.floor`, `tf.greater`, `tf.greater_equal`, `tf.less`, > `tf.less_equal`, `tf.log`, `tf.logp1`, `tf.logical_and`, > `tf.logical_not`, `tf.logical_or`, `tf.maximum`, `tf.minimum`, > `tf.not_equal`, `tf.sin`, `tf.sinh`, `tf.tan` > * Deprecate `tf.data.Dataset.shard`. > * Deprecate `saved_model.loader.load` which is replaced by > `saved_model.load` and `saved_model.main_op`, which will be replaced by > `saved_model.main_op` in V2. > * Deprecate tf.QUANTIZED_DTYPES. The official new symbol is > tf.dtypes.QUANTIZED_DTYPES. > * Update sklearn imports for deprecated packages. > * Deprecate `Variable.count_up_to` and `tf.count_up_to` in favor of > `Dataset.range`. > * Export `confusion_matrix` op as `tf.math.confusion_matrix` instead of > `tf.train.confusion_matrix`. > * Add `tf.dtypes.` endpoint for every constant in dtypes.py. Moving > endpoints in versions.py to corresponding endpoints in `tf.sysconfig.` > ... (truncated)Commits
- [`6b63465`](https://github.com/tensorflow/tensorflow/commit/6b634657d8ff1355132c3838271e4f569d1ffaba) Merge pull request [#27959](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27959) from tensorflow/update-release-notes-version - [`e967833`](https://github.com/tensorflow/tensorflow/commit/e9678339c906d2ffe78a266de23b45348f0087a6) Update header on release notes - [`cf74798`](https://github.com/tensorflow/tensorflow/commit/cf74798993f545456cb50ec188f4e25e4b4514c1) Merge pull request [#27958](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27958) from tensorflow/update-release-version - [`7fba173`](https://github.com/tensorflow/tensorflow/commit/7fba173bcd049c6f6aa871e3ba2e914d38ea20a3) Update version to 1.12.2 - [`332f080`](https://github.com/tensorflow/tensorflow/commit/332f080651162a202069b633d13c6f2e95db63b6) Merge pull request [#27878](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27878) from tensorflow/windows-cpu - [`c9fcc49`](https://github.com/tensorflow/tensorflow/commit/c9fcc49f5af7ea1985043307a67e8094cde81556) Fix windows build for CPU too - [`416b4a3`](https://github.com/tensorflow/tensorflow/commit/416b4a3398e814c0abf3101e0d803920852a9bd0) Merge pull request [#27873](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27873) from tensorflow/more-bazel-incompatible-flags - [`3ebe165`](https://github.com/tensorflow/tensorflow/commit/3ebe165f0bfc62aa0004ffa4d5a15ca4da5029c3) Add --incompatible_disable_cc_toolchain_label_from_crosstool_proto=false flag - [`5ab9466`](https://github.com/tensorflow/tensorflow/commit/5ab94660a4da3632d5514509d3353d54cbf2e87d) Reformat bazel invocation lines - [`446d393`](https://github.com/tensorflow/tensorflow/commit/446d3932ffbee93aca87a68427f935d6e598ab14) Merge pull request [#27870](https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/27870) from tensorflow/bazel-http-archive - Additional commits viewable in [compare view](https://github.com/tensorflow/tensorflow/compare/v1.11.0...v1.12.2)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 ignore this [patch|minor|major] version` will close this PR and stop Dependabot creating any more for this minor/major 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/phenompeople/bert-server/network/alerts).