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jayfurmanek committed Jul 10, 2024
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1 change: 1 addition & 0 deletions .bazelrc
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Expand Up @@ -631,6 +631,7 @@ try-import %workspace%/.bazelrc.user
# Here are bazelrc configs for release builds
# Build TensorFlow v2.
test:release_base --test_size_filters=small,medium
test:release_base --flaky_test_attempts=3

# Ensure release_base is set on linux
build:release_linux_base --config=release_base
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141 changes: 16 additions & 125 deletions RELEASE.md
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Expand Up @@ -2,125 +2,52 @@

## TensorFlow

<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>

### Breaking Changes

* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>

### Known Caveats

* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE>

### Major Features and Improvements

* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>

* GPU
* Support for NVIDIA GPUs with compute capability 8.9 (e.g. L4 & L40) has
been added to TF binary distributions (Python wheels).
* Replace `DebuggerOptions` of TensorFlow Quantizer, and migrate to
`DebuggerConfig` of StableHLO Quantizer.
* Add TensorFlow to StableHLO converter to TensorFlow pip package.
* TensorRT support: this is the last release supporting TensorRT. It will be
removed in the next release.
* NumPy 2.0 support: TensorFlow is going to support NumPy 2.0 in the next
release. It may break some edge cases of TensorFlow API usage.

## Keras

<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>

### Breaking Changes

* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>
* GPU
* Support for NVIDIA GPUs with compute capability 5.x (Maxwell generation)
has been removed from TF binary distributions (Python wheels).

### Known Caveats

* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE>
* Support for NVIDIA GPUs with compute capability 5.x (Maxwell generation) has been removed from TF binary distributions (Python wheels).

### Major Features and Improvements

* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

* Add `is_cpu_target_available`, which indicates whether or not TensorFlow was
built with support for a given CPU target. This can be useful for skipping
target-specific tests if a target is not supported.
* Add `is_cpu_target_available`, which indicates whether or not TensorFlow was built with support for a given CPU target. This can be useful for skipping target-specific tests if a target is not supported.

* `tf.data`
* Support `data.experimental.distribued_save`. `distribued_save` uses
tf.data service
(https://www.tensorflow.org/api_docs/python/tf/data/experimental/service)
to write distributed dataset snapshots. The call is non-blocking and
returns without waiting for the snapshot to finish. Setting `wait=True` to
`tf.data.Dataset.load` allows the snapshots to be read while they are
being written.
* Support `data.experimental.distribued_save`. `distribued_save` uses tf.data service (https://www.tensorflow.org/api_docs/python/tf/data/experimental/service) to write distributed dataset snapshots. The call is non-blocking and returns without waiting for the snapshot to finish. Setting `wait=True` to `tf.data.Dataset.load` allows the snapshots to be read while they are being written.

### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>
* GPU
* Support for NVIDIA GPUs with compute capability 8.9 (e.g. L4 & L40) has been added to TF binary distributions (Python wheels).
* Replace `DebuggerOptions` of TensorFlow Quantizer, and migrate to `DebuggerConfig` of StableHLO Quantizer.
* Add TensorFlow to StableHLO converter to TensorFlow pip package.
* TensorRT support: this is the last release supporting TensorRT. It will be removed in the next release.
* NumPy 2.0 support: TensorFlow is going to support NumPy 2.0 in the next release. It may break some edge cases of TensorFlow API usage.

* `tf.lite`
* Quantization for `FullyConnected` layer is switched from per-tensor to
per-channel scales for dynamic range quantization use case (`float32`
inputs / outputs and `int8` weights). The change enables new quantization
schema globally in the converter and inference engine. The new behaviour
can be disabled via experimental
flag `converter._experimental_disable_per_channel_quantization_for_dense_layers = True`.
* Quantization for `FullyConnected` layer is switched from per-tensor to per-channel scales for dynamic range quantization use case (`float32` inputs / outputs and `int8` weights). The change enables new quantization schema globally in the converter and inference engine. The new behaviour can be disabled via experimental flag `converter._experimental_disable_per_channel_quantization_for_dense_layers = True`.
* C API:
* The experimental `TfLiteRegistrationExternal` type has been renamed as
`TfLiteOperator`, and likewise for the corresponding API functions.
* The Python TF Lite Interpreter bindings now have an option
`experimental_default_delegate_latest_features` to enable all default
delegate features.
* The experimental `TfLiteRegistrationExternal` type has been renamed as `TfLiteOperator`, and likewise for the corresponding API functions.
* The Python TF Lite Interpreter bindings now have an option `experimental_default_delegate_latest_features` to enable all default delegate features.
* Flatbuffer version update:
* `GetTemporaryPointer()` bug fixed.

* `tf.data`
* Add `wait` to `tf.data.Dataset.load`. If `True`, for snapshots written
with `distributed_save`, it reads the snapshot while it is being written.
For snapshots written with regular `save`, it waits for the snapshot until
it's finished. The default is `False` for backward compatibility. Users of
`distributed_save` are recommended to set it to `True`.
* Add `wait` to `tf.data.Dataset.load`. If `True`, for snapshots written with `distributed_save`, it reads the snapshot while it is being written. For snapshots written with regular `save`, it waits for the snapshot until it's finished. The default is `False` for backward compatibility. Users of `distributed_save` are recommended to set it to `True`.

* `tf.tpu.experimental.embedding.TPUEmbeddingV2`
* Add `compute_sparse_core_stats` for sparse core users to profile the
data with this API to get the `max_ids` and `max_unique_ids`. These
numbers will be needed to configure the sparse core embedding mid level
api.
* Add `compute_sparse_core_stats` for sparse core users to profile the data with this API to get the `max_ids` and `max_unique_ids`. These numbers will be needed to configure the sparse core embedding mid level api.
* Remove the `preprocess_features` method since that's no longer needed.

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as:

<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
Abdulaziz Aloqeely, Ahmad-M-Al-Khateeb, Akhil Goel, akhilgoe, Alexander Pivovarov, Amir Samani, Andrew Goodbody, Andrey Portnoy, Ashiq Imran, Ben Olson, Chao, Chase Riley Roberts, Clemens Giuliani, dependabot[bot], Dimitris Vardoulakis, Dragan Mladjenovic, ekuznetsov139, Elfie Guo, Faijul Amin, Gauri1 Deshpande, Georg Stefan Schmid, guozhong.zhuang, Hao Wu, Haoyu (Daniel), Harsha H S, Harsha Hs, Harshit Monish, Ilia Sergachev, Jane Liu, Jaroslav Sevcik, Jinzhe Zeng, Justin Dhillon, Kaixi Hou, Kanvi Khanna, LakshmiKalaKadali, Learning-To-Play, lingzhi98, Lu Teng, Matt Bahr, Max Ren, Meekail Zain, Mmakevic-Amd, mraunak, neverlva, nhatle, Nicola Ferralis, Olli Lupton, Om Thakkar, orangekame3, ourfor, pateldeev, Pearu Peterson, pemeliya, Peng Sun, Philipp Hack, Pratik Joshi, prrathi, rahulbatra85, Raunak, redwrasse, Robert Kalmar, Robin Zhang, RoboSchmied, Ruturaj Vaidya, sachinmuradi, Shawn Wang, Sheng Yang, Surya, Thibaut Goetghebuer-Planchon, Thomas Preud'Homme, tilakrayal, Tj Xu, Trevor Morris, wenchenvincent, Yimei Sun, zahiqbal, Zhu Jianjiang, Zoranjovanovic-Ns

# Release 2.16.0

## TensorFlow

<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>

* TensorFlow Windows Build:

* Clang is now the default compiler to build TensorFlow CPU wheels on the
Expand All @@ -133,9 +60,6 @@ This release contains contributions from many people at Google, as well as:

### Breaking Changes

* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>

* `tf.summary.trace_on` now takes a `profiler_outdir` argument. This must be
set if `profiler` arg is set to `True`.

Expand Down Expand Up @@ -173,18 +97,11 @@ This release contains contributions from many people at Google, as well as:

### Known Caveats

* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE>

* Full aarch64 Linux and Arm64 macOS wheels are now published to the
`tensorflow` pypi repository and no longer redirect to a separate package.

### Major Features and Improvements

* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

* Support for Python 3.12 has been added.
* [tensorflow-tpu](https://pypi.org/project/tensorflow-tpu/) package is now
available for easier TPU based installs.
Expand All @@ -193,10 +110,6 @@ This release contains contributions from many people at Google, as well as:

### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>

* `tf.lite`
* Added support for `stablehlo.gather`.
* Added support for `stablehlo.add`.
Expand Down Expand Up @@ -272,33 +185,11 @@ This release contains contributions from many people at Google, as well as:
* Added the option to set adaptive epsilon to match implementations with Jax
and PyTorch equivalents.

### Breaking Changes

* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>

### Known Caveats

* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE>

### Major Features and Improvements

* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as:

RoboTux, <INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
Aakar Dwivedi, Akhil Goel, Alexander Grund, Alexander Pivovarov, Andrew Goodbody, Andrey Portnoy, Aneta Kaczyńska, AnetaKaczynska, ArkadebMisra, Ashiq Imran, Ayan Moitra, Ben Barsdell, Ben Creech, Benedikt Lorch, Bhavani Subramanian, Bianca Van Schaik, Chao, Chase Riley Roberts, Connor Flanagan, David Hall, David Svantesson, David Svantesson-Yeung, dependabot[bot], Dr. Christoph Mittendorf, Dragan Mladjenovic, ekuznetsov139, Eli Kobrin, Eugene Kuznetsov, Faijul Amin, Frédéric Bastien, fsx950223, gaoyiyeah, Gauri1 Deshpande, Gautam, Giulio C.N, guozhong.zhuang, Harshit Monish, James Hilliard, Jane Liu, Jaroslav Sevcik, jeffhataws, Jerome Massot, Jerry Ge, jglaser, jmaksymc, Kaixi Hou, kamaljeeti, Kamil Magierski, Koan-Sin Tan, lingzhi98, looi, Mahmoud Abuzaina, Malik Shahzad Muzaffar, Meekail Zain, mraunak, Neil Girdhar, Olli Lupton, Om Thakkar, Paul Strawder, Pavel Emeliyanenko, Pearu Peterson, pemeliya, Philipp Hack, Pierluigi Urru, Pratik Joshi, radekzc, Rafik Saliev, Ragu, Rahul Batra, rahulbatra85, Raunak, redwrasse, Rodrigo Gomes, ronaghy, Sachin Muradi, Shanbin Ke, shawnwang18, Sheng Yang, Shivam Mishra, Shu Wang, Strawder, Paul, Surya, sushreebarsa, Tai Ly, talyz, Thibaut Goetghebuer-Planchon, Tj Xu, Tom Allsop, Trevor Morris, Varghese, Jojimon, weihanmines, wenchenvincent, Wenjie Zheng, Who Who Who, Yasir Ashfaq, yasiribmcon, Yoshio Soma, Yuanqiang Liu, Yuriy Chernyshov

# Release 2.15.0.post1

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2 changes: 1 addition & 1 deletion ci/official/envs/nightly_upload
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Expand Up @@ -22,7 +22,7 @@ TFCI_ARTIFACT_FINAL_PYPI_ARGS="--config-file=$KOKORO_KEYSTORE_DIR/73361_tensorfl
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/nightly/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-artifact-staging/staging/nightly/$(git rev-parse HEAD)/"
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-staging/staging/nightly/$(git rev-parse HEAD)/"

# 2. The internal version numbers get changed
TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=1
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2 changes: 1 addition & 1 deletion ci/official/envs/versions_upload
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Expand Up @@ -23,6 +23,6 @@ TFCI_ARTIFACT_FINAL_PYPI_ARGS="--config-file=$KOKORO_KEYSTORE_DIR/73361_tensorfl
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/versions/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-artifact-staging/staging/versions/${_LOUHI_EXECUTION_ID:-$(git rev-parse HEAD)}/"
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-staging/staging/versions/${_LOUHI_EXECUTION_ID:-$(git rev-parse HEAD)}/"

TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config resultstore"
5 changes: 3 additions & 2 deletions ci/official/requirements_updater/requirements.in
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Expand Up @@ -13,13 +13,14 @@ gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.4.0, < 0.5.0

# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.0.0.dev
tb-nightly ~= 2.17.0.a
keras ~= 3.2.0
tensorboard ~= 2.17.0

# Test dependencies
grpcio >= 1.24.3, < 2.0
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