Merge branch 'master' into kanvi/MLIR-ConvSqueezeBias

.bazelrc

@@ -398,11 +398,6 @@ build:windows --verbose_failures
 # See: https://github.com/bazelbuild/bazel/issues/5163
 build:windows --features=compiler_param_file
 
-# On windows, we never cross compile
-build:windows --distinct_host_configuration=false
-# On linux, don't cross compile by default
-build:linux --distinct_host_configuration=false
-
 # Do not risk cache corruption. See:
 # https://github.com/bazelbuild/bazel/issues/3360
 build:linux --experimental_guard_against_concurrent_changes
@@ -443,7 +438,6 @@ build:rbe --bes_backend=buildeventservice.googleapis.com
 build:rbe --bes_results_url="https://source.cloud.google.com/results/invocations"
 build:rbe --bes_timeout=600s
 build:rbe --define=EXECUTOR=remote
-build:rbe --distinct_host_configuration=false
 build:rbe --flaky_test_attempts=3
 build:rbe --jobs=800
 build:rbe --remote_executor=grpcs://remotebuildexecution.googleapis.com
@@ -557,8 +551,8 @@ build:rbe_linux_py3_base --python_path="/usr/local/bin/python3.9"
 build:rbe_linux_py3_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"
 
 build:rbe_win --config=rbe
-build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_01232023:toolchain"
-build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_01232023:cc-toolchain-x64_windows"
+build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_02232023:toolchain"
+build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_02232023:cc-toolchain-x64_windows"
 build:rbe_win --extra_execution_platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
 build:rbe_win --host_platform="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
 build:rbe_win --platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
@@ -610,10 +604,8 @@ build:elinux --crosstool_top=@local_config_embedded_arm//:toolchain
 build:elinux --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
 build:elinux_aarch64 --config=elinux
 build:elinux_aarch64 --cpu=aarch64
-build:elinux_aarch64 --distinct_host_configuration=true
 build:elinux_armhf --config=elinux
 build:elinux_armhf --cpu=armhf
-build:elinux_armhf --distinct_host_configuration=true
 build:elinux_armhf --copt -mfp16-format=ieee
 # END TF REMOTE BUILD EXECUTION OPTIONS
 
@@ -627,7 +619,6 @@ try-import %workspace%/.bazelrc.user
 
 # Here are bazelrc configs for release builds
 build:release_base --config=v2
-build:release_base --distinct_host_configuration=false
 test:release_base --flaky_test_attempts=3
 test:release_base --test_size_filters=small,medium
 
@@ -705,4 +696,4 @@ build:tf_fuzztest --action_env=CC=clang
 build:tf_fuzztest --action_env=CXX=clang++
 build:tf_fuzztest --spawn_strategy=sandboxed
 build:tf_fuzztest --config=monolithic
-build:tf_fuzztest --@libjpeg_turbo//:noasm=yes
+build:tf_fuzztest --@libjpeg_turbo//:noasm=yes

.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml

@@ -1,5 +1,5 @@
 name: Tensorflow Issue Template
-description: Use this template to report any issue
+description: Please report security related issue using [Google Bug Hunters reporting form](https://bughunters.google.com/). To report any other TensorFlow related issue please use this template.
 body:
   - type: dropdown
     id: issue-type

.github/bot_config.yml

@@ -17,8 +17,8 @@
 assignees:
    - synandi
    - tiruk007
-   - gaikwadrahul8
-   - pjpratik
+   - tilakrayal
+   - sushreebarsa
 # A list of assignees for compiler folder
 compiler_assignees:
    - joker-eph

.github/workflows/stale-issues.yml

@@ -0,0 +1,64 @@
+# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+name: Close inactive issues
+on:
+  schedule:
+    - cron: "30 1 * * *"
+
+jobs:
+  close-issues:
+    # Don't do this in forks
+    if: github.repository == 'tensorflow/tensorflow'
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+      - name: Awaiting response issues
+        uses: actions/stale@v5
+        with:
+          days-before-issue-stale: 7
+          days-before-issue-close: 7
+          stale-issue-label: "stale"
+          # reason for closed the issue default value is not_planned
+          close-issue-reason: completed
+          only-labels: "stat:awaiting response"
+          stale-issue-message: > 
+            This issue is stale because it has been open for 7 days with no activity.
+            It will be closed if no further activity occurs. Thank you.
+          close-issue-message: >
+            This issue was closed because it has been inactive for 7 days since being marked as stale.
+            Please reopen if you'd like to work on this further.
+          days-before-pr-stale: 14
+          days-before-pr-close: 14
+          stale-pr-message: "This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you."
+          close-pr-message: "This PR was closed because it has been inactive for 14 days since being marked as stale. Please reopen if you'd like to work on this further."
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+      - name: Contribution issues
+        uses: actions/stale@v5
+        with:
+          days-before-issue-stale: 180
+          days-before-issue-close: 365
+          stale-issue-label: "stale"
+          # reason for closed the issue default value is not_planned
+          close-issue-reason: completed
+          any-of-labels: "stat:contribution welcome,stat:good first issue"
+          stale-issue-message: > 
+            This issue is stale because it has been open for 180 days with no activity.
+            It will be closed if no further activity occurs. Thank you.
+          close-issue-message: >
+            This issue was closed because it has been inactive for 1 year.
+          repo-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/trusted-partners.yml

@@ -52,6 +52,9 @@ jobs:
             case "linaro.org":
               console.log(await script.filter({github, context, domain}));
               break;
+            case "arm.com":
+              console.log(await script.filter({github, context, domain}));
+              break;
             case "google.com":
               console.log("Googler. No action necessary");
               break;

.github/workflows/trusted_partners.js

@@ -85,6 +85,10 @@ const filter_action = async ({github, context, domain}) => {
       assignees.push('nitins17', 'penpornk');
     }
   }
+  if (lowercased_title.includes('tf-mot') && lowercased_title.includes('arm') &&
+      domain.includes('arm.com')) {
+    assignees.push('rino20', 'yyoon', 'lenscloth');
+  }
 
   const resp_label = await github.rest.issues.addLabels({
     issue_number: context.issue.number,

README.md

@@ -9,6 +9,7 @@
 [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/tensorflow/tensorflow/badge)](https://api.securityscorecards.dev/projects/github.com/tensorflow/tensorflow)
 [![Fuzzing Status](https://oss-fuzz-build-logs.storage.googleapis.com/badges/tensorflow.svg)](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow)
 [![Fuzzing Status](https://oss-fuzz-build-logs.storage.googleapis.com/badges/tensorflow-py.svg)](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow-py)
+[![OSSRank](https://shields.io/endpoint?url=https://ossrank.com/shield/44)](https://ossrank.com/p/44)
 [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-v1.4%20adopted-ff69b4.svg)](CODE_OF_CONDUCT.md)
 
 **`Documentation`** |

RELEASE.md

@@ -1,3 +1,152 @@
+# Release 2.13.0
+
+## Breaking Changes
+
+* <DOCUMENT BREAKING CHANGES HERE>
+* <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>
+
+*  `tf.keras`
+
+    *  Removed the Keras scikit-learn API wrappers (`KerasClassifier` and
+       `KerasRegressor`), which had been deprecated in August 2021.
+       We recommend using [SciKeras](https://github.com/adriangb/scikeras)
+       instead.
+    *  The default Keras model saving format is now the Keras v3 format:
+       calling `model.save("xyz.keras")` will no longer create a H5 file,
+       it will create a native Keras model file.
+       This will only be breaking for you if you were manually inspecting or
+       modifying H5 files saved by Keras under a `.keras` extension.
+       If this breaks you, simply add `save_format="h5"` to your `.save()` call
+       to revert back to the prior behavior.
+
+* The LMDB kernels have been changed to return an error. This is in preparation
+  for completely removing them from TensorFlow. The LMDB dependency that these
+  kernels are bringing to TensorFlow has been dropped, thus making the build
+  slightly faster and more secure.
+
+## 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
+
+*   `tf.lite`:
+
+    *   Add 16-bit and 64-bit float type support for built-in op `cast`.
+    *   The Python TF Lite Interpreter bindings now have an option
+        `experimental_disable_delegate_clustering` to turn-off delegate
+        clustering.
+    *   Add int16x8 support for the built-in op `exp`
+    *   Add int16x8 support for the built-in op `mirror_pad`
+    *   Add 16-bit int type support for built-in op `less`, `greater_than`,
+        `equal`
+    *   Add 8-bit and 16-bit support for `floor_div` and `floor_mod`.
+    *   Add int16 indices support for built-in op `gather` and `gather_nd`.
+    *   Add reference implementation for 16-bit int unquantized `add`.
+
+*   `tf.keras`
+
+    *   Added F-Score metrics `tf.keras.metrics.FBetaScore`,
+        `tf.keras.metrics.F1Score`, and `tf.keras.metrics.R2Score`.
+    *   Added activation function `tf.keras.activations.mish`.
+    *   Added experimental `keras.metrics.experimental.PyMetric` API for metrics
+        that run Python code on the host CPU (compiled outside of the TensorFlow
+        graph). This can be used for integrating metrics from external Python
+        libraries (like sklearn or pycocotools) into Keras as first-class Keras
+        metrics.
+    *   Added `tf.keras.optimizers.Lion` optimizer.
+    *   The `SidecarEvaluatorModelExport` callback has been added to Keras as
+        `keras.callbacks.SidecarEvaluatorModelExport`. This callback allows for
+        exporting the model the best-scoring model as evaluated by a
+        `SidecarEvaluator` evaluator. The evaluator regularly evaluates the
+        model and exports it if the user-defined comparison function determines
+        that it is an improvement.
+    *   Added warmup capabilities to `tf.keras.optimizers.schedules.CosineDecay`
+        learning rate scheduler. You can now specify an initial and target
+        learning rate, and our scheduler will perform a linear interpolation
+        between the two after which it will begin a decay phase.
+    *   Added experimental support for an exactly-once visitation guarantee for
+        evaluating Keras models trained with
+        `tf.distribute.ParameterServerStrategy`, via the
+        `exact_evaluation_shards` argument in `Model.fit` and `Model.evaluate`.
+    *   Added `tf.keras.__internal__.KerasTensor`,
+        `tf.keras.__internal__.SparseKerasTensor`, and
+        `tf.keras.__internal__.RaggedKerasTensor` classes. You can use these
+        classes to do instance type checking and type annotations for
+        layer/model inputs and outputs.
+    *   All the `tf.keras.dtensor.experimental.optimizers` classes have been 
+        merged with `tf.keras.optimizers`. You can migrate your code to use
+        `tf.keras.optimizers` directly. The API namespace for
+        `tf.keras.dtensor.experimental.optimizers` will be removed in future
+        releases.
+
+*   `tf.function`:
+
+    *   ConcreteFunction (`tf.types.experimental.ConcreteFunction`) as generated
+        through `get_concrete_function` now performs holistic input validation
+        similar to calling `tf.function` directly. This can cause breakages
+        where existing calls pass Tensors with the wrong shape or omit certain
+        non-Tensor arguments (including default values).
+
+*   `tf.nn`
+
+    *   `tf.nn.embedding_lookup_sparse` and `tf.nn.safe_embedding_lookup_sparse`
+        now support ids and weights described by `tf.RaggedTensor`s.
+    *   Added a new boolean argument `allow_fast_lookup` to
+        `tf.nn.embedding_lookup_sparse` and
+        `tf.nn.safe_embedding_lookup_sparse`, which enables a simplified and
+        typically faster lookup procedure.
+
+*   `tf.data`
+
+    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e.
+        `Dataset.zip(a, b, c)`.
+
+*   `tf.SavedModel`
+
+    *   Introduce class method
+        `tf.saved_model.experimental.Fingerprint.from_proto(proto)`, which can
+        be used to construct a `Fingerprint` object directly from a protobuf.
+    *   Introduce member method
+        `tf.saved_model.experimental.Fingerprint.singleprint()`, which provides
+        a convenient way to uniquely identify a SavedModel.
+
+## 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.distribute`
+
+    *   Opened an experimental API,
+        `tf.distribute.experimental.coordinator.get_current_worker_index`, for
+        retrieving the worker index from within a worker, when using parameter
+        server training with a custom training loop.
+
+*   `tf.experimental.dtensor`:
+
+    *   Deprecated `dtensor.run_on` in favor of `dtensor.default_mesh` to
+        correctly indicate that the context does not override the mesh that the
+        ops and functions will run on, it only sets a fallback default mesh.
+    *   List of members of dtensor.Layout and dtensor.Mesh have slightly changed
+        as part of efforts to consolidate the C++ and Python source
+        code with pybind11. Most notably, Layout.serialized_string is removed.
+
+*   `tf.experimental.ExtensionType`:
+
+    *   `tf.experimental.ExtensionType` now supports Python `tuple` as
+        the type annotation of its fields.
+
+## Thanks to our Contributors
+
+This release contains contributions from many people at Google, as well as:
+
+<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
+
+
 # Release 2.12.0
 
 # Breaking Changes
@@ -159,7 +308,15 @@
         `rerandomize_each_iteration=True`, the `sample_from_datasets()`
         operation will use a different (deterministic) sequence of numbers every
         epoch.
-
+    *   Added a new field, `warm_start`, to
+        `tf.data.experimental.OptimizationOptions`. If it is set to `True`,
+        tf.data will start background threads of asynchronous
+        transformations upon iterator creation (as opposed to upon first call
+        to `GetNext`). To enable this behavior, set `warm_start=True` in
+        `tf.data.experimental.OptimizationOptions`. It should be noted that this
+        possibly improves the latency of the initial 'GetNext' call at the
+        expense of requiring more memory to hold prefetched elements between
+        the time of iterator construction and usage.
 *   `tf.test`:
 
     *   Added `tf.test.experimental.sync_devices`, which is useful for
@@ -1574,7 +1731,7 @@ This releases introduces several vulnerability fixes:
     ([CVE-2022-23572](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23572))
 *   Fixes a heap OOB read/write in `SpecializeType`
     ([CVE-2022-23574](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23574))
-*   Fixes an unitialized variable access in `AssignOp`
+*   Fixes an uninitialized variable access in `AssignOp`
     ([CVE-2022-23573](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23573))
 *   Fixes an integer overflow in `OpLevelCostEstimator::CalculateTensorSize`
     ([CVE-2022-23575](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23575))
@@ -1852,7 +2009,7 @@ This releases introduces several vulnerability fixes:
     ([CVE-2022-23572](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23572))
 *   Fixes a heap OOB read/write in `SpecializeType`
     ([CVE-2022-23574](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23574))
-*   Fixes an unitialized variable access in `AssignOp`
+*   Fixes an uninitialized variable access in `AssignOp`
     ([CVE-2022-23573](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23573))
 *   Fixes an integer overflow in `OpLevelCostEstimator::CalculateTensorSize`
     ([CVE-2022-23575](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23575))