Merge pull request #2271 from ROCmSoftwarePlatform/develop-upstream-s…

…ync-231019

Develop upstream sync 231019

.bazelrc

@@ -426,7 +426,18 @@ build:verbose_logs --output_filter=
 #   avoid having to define linux/win separately.
 build:avx_linux --copt=-mavx
 build:avx_linux --host_copt=-mavx
-build:avx_win --copt=/arch=AVX
+build:avx_win --copt=/arch:AVX
+
+# Use Clang-cl compiler on Windows
+build:win_clang --copt=/clang:-Weverything
+build:win_clang --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
+build:win_clang --extra_execution_platforms=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
+build:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
+build:win_clang --compiler=clang-cl
+build:win_clang --linkopt=/FORCE:MULTIPLE
+build:win_clang --host_linkopt=/FORCE:MULTIPLE
+test:win_clang --linkopt=/FORCE:MULTIPLE
+test:win_clang --host_linkopt=/FORCE:MULTIPLE
 
 # Options to build TensorFlow 1.x or 2.x.
 # TODO(kanglan): Change v2's define to default behavior
@@ -636,6 +647,7 @@ build:release_arm64_linux --config=linux_arm64
 build:release_arm64_linux --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"
 build:release_arm64_linux --config=mkl_aarch64_threadpool
 build:release_arm64_linux --copt=-flax-vector-conversions
+test:release_arm64_linux --flaky_test_attempts=3
 
 # The old gcc linux build options are preserved in the unsupported_*_linux
 # configs. If your project fails to build with Clang, you can use these

CONTRIBUTING.md

@@ -232,13 +232,20 @@ There are two ways to run TensorFlow unit tests.
     and
     [GPU developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile)
     for the required packages. Alternatively, use the said
-    [Docker images](https://hub.docker.com/r/tensorflow/tensorflow/tags/), e.g.,
-    `tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` for
+    [tensorflow/build Docker images](https://hub.docker.com/r/tensorflow/build)
+    (`tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` are no
+    longer supported for) development. Use TF SIG Build Dockerfiles in
     development to avoid installing the packages directly on your system (in
     which case remember to change the directory from `/root` to `/tensorflow`
     once you get into the running container so `bazel` can find the `tensorflow`
     workspace).
 
+    you can do this by using the following command. As an example-
+
+    ```bash
+    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
+    ```
+
     Once you have the packages installed, you can run a specific unit test in
     bazel by doing as follows:
 

RELEASE.md

@@ -1,4 +1,4 @@
-# Release 2.15.0
+# Release 2.16.0
 
 ## TensorFlow
 
@@ -9,8 +9,31 @@
 * <DOCUMENT BREAKING CHANGES HERE>
 * <THIS SECTION SHOULD CONTAIN API, ABI AND BEHAVIORAL BREAKING CHANGES>
 
-* `tf.types.experimental.GenericFunction` has been renamed to
-  `tf.types.experimental.PolymorphicFunction`.
+### 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>
+
+## 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>
 
 ### Known Caveats
 
@@ -23,54 +46,60 @@
 *   <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:
+
+<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
+
+# Release 2.15.0
+
+## TensorFlow
+
+### Breaking Changes
+
+* `tf.types.experimental.GenericFunction` has been renamed to `tf.types.experimental.PolymorphicFunction`.
+
+### Known Caveats
+
+### Major Features and Improvements
+
 *   [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md)
     Windows x64 & x86.
 
     *   **Windows x64 & x86 packages:**
         *   oneDNN optimizations are *enabled by default* on X86 CPUs
-    *   To explicitly enable or disable oneDNN optimizations, set the
-        environment variable `TF_ENABLE_ONEDNN_OPTS` to `1` (enable) or `0`
-        (disable) before running TensorFlow. To fall back to default settings,
-        unset the environment variable.
-    *   oneDNN optimizations can yield slightly different numerical results from
-        without oneDNN optimizations due to floating-point round-off errors from
-        different computation approaches and orders.
-    *   To verify if oneDNN optimizations are on, look for a message with
-        *"oneDNN custom operations are on"* in the log. If the exact phrase is
-        not there, it means they are off.
+    *   To explicitly enable or disable oneDNN optimizations, set the environment variable `TF_ENABLE_ONEDNN_OPTS` to `1` (enable) or `0` (disable) before running TensorFlow. To fall back to default settings, unset the environment variable.
+    *   oneDNN optimizations can yield slightly different numerical results compared to when oneDNN optimizations are disabled due to floating-point round-off errors from
+ different computation approaches and orders.
+    *   To verify if oneDNN optimizations are on, look for a message with *"oneDNN custom operations are on"* in the log. If the exact phrase is not there, it means they are off.
 
 * Making the `tf.function` type system fully available:
 
-    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to
-       declare Tensor decomposition and type casting support.
-    * Introducing `tf.types.experimental.FunctionType` as the comprehensive
-      representation of the signature of `tf.function` callables. It can be
-      accessed through the `function_type` property of `tf.function`s and
-      `ConcreteFunction`s. See the `tf.types.experimental.FunctionType`
-      documentation for more details.
+    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.
+    * Introducing `tf.types.experimental.FunctionType` as the comprehensive representation of the signature of `tf.function` callables. It can be accessed through the `function_type` property of `tf.function`s and `ConcreteFunction`s. See the `tf.types.experimental.FunctionType` documentation for more details.
 
-* Introducing `tf.types.experimental.AtomicFunction` as the fastest way to
-  perform TF computations in Python.
+* Introducing `tf.types.experimental.AtomicFunction` as the fastest way to perform TF computations in Python.
 
     * Can be accessed through `inference_fn` property of `ConcreteFunction`s
     * Does not support gradients.
-    * See `tf.types.experimental.AtomicFunction` documentation for how to call
-      and use it.
-
+    * See `tf.types.experimental.AtomicFunction` documentation for how to call and use it.
 
 *   `tf.data`:
 
-    *   Moved option `warm_start` from
-        `tf.data.experimental.OptimizationOptions` to `tf.data.Options`.
+    *   Moved option `warm_start` from `tf.data.experimental.OptimizationOptions` to `tf.data.Options`.
 
 *   `tf.lite`:
 
     *   `sub_op` and `mul_op` support broadcasting up to 6 dimensions.
 
-    *  The `tflite::SignatureRunner` class, which provides support for named
-       parameters and for multiple named computations within a single TF Lite
-       model, is no longer considered experimental. Likewise for the following
-       signature-related methods of `tflite::Interpreter`:
+    *  The `tflite::SignatureRunner` class, which provides support for named parameters and for multiple named computations within a single TF Lite model, is no longer considered experimental. Likewise for the following signature-related methods of `tflite::Interpreter`:
 
        *   `tflite::Interpreter::GetSignatureRunner`
        *   `tflite::Interpreter::signature_keys`
@@ -79,8 +108,7 @@
        *   `tflite::Interpreter::input_tensor_by_signature`
        *   `tflite::Interpreter::output_tensor_by_signature`
 
-    *  Similarly, the following signature runner functions in the TF Lite C API
-       are no longer considered experimental:
+    *  Similarly, the following signature runner functions in the TF Lite C API are no longer considered experimental:
 
        *    `TfLiteInterpreterGetSignatureCount`
        *    `TfLiteInterpreterGetSignatureKey`
@@ -95,80 +123,47 @@
        *    `TfLiteSignatureRunnerInvoke`
        *    `TfLiteSignatureRunnerResizeInputTensor`
 
-    * New C API function `TfLiteExtensionApisVersion` added to
-      `tensorflow/lite/c/c_api.h`.
+    * New C API function `TfLiteExtensionApisVersion` added to `tensorflow/lite/c/c_api.h`.
 
     * Add int8 and int16x8 support for RSQRT operator
 
 * Android NDK r25 is supported.
 
 ### 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>
-
 *   Add TensorFlow Quantizer to TensorFlow pip package.
 
-*   `tf.sparse.segment_sum` `tf.sparse.segment_mean` `tf.sparse.segment_sqrt_n`
-    `SparseSegmentSum/Mean/SqrtN[WithNumSegments]`
+*   `tf.sparse.segment_sum` `tf.sparse.segment_mean` `tf.sparse.segment_sqrt_n` `SparseSegmentSum/Mean/SqrtN[WithNumSegments]`
 
-    *   Added `sparse_gradient` option (default=false) that makes the gradient
-        of these functions/ops sparse (`IndexedSlices`) instead of dense
-        (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.
+    *   Added `sparse_gradient` option (default=false) that makes the gradient of these functions/ops sparse (`IndexedSlices`) instead of dense (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.
 
 *   `tf.nn.embedding_lookup_sparse`
 
     *   Optimized this function for some cases by fusing internal operations.
 
 *   `tf.saved_model.SaveOptions`
 
-    *   Provided a new `experimental_skip_saver` argument which, if specified,
-        will suppress the addition of `SavedModel`-native save and restore ops
-        to the `SavedModel`, for cases where users already build custom
-        save/restore ops and checkpoint formats for the model being saved, and
-        the creation of the SavedModel-native save/restore ops simply cause
-        longer model serialization times.
+    *   Provided a new `experimental_skip_saver` argument which, if specified, will suppress the addition of `SavedModel`-native save and restore ops to the `SavedModel`, for cases where users already build custom save/restore ops and checkpoint formats for the model being saved, and the creation of the SavedModel-native save/restore ops simply cause longer model serialization times.
 
-## Keras
+* `tf.math.bincount`
+    *   Updated documentation. Fixed "[Bincount doesn't check the tensor type](https://github.com/tensorflow/tensorflow/issues/56499)" and some other corner cases.
 
-<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>
+## Keras
 
 ### 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>
-
 * Add ops to `tensorflow.raw_ops` that were missing.
 * `tf.CheckpointOptions`
-    * It now takes in a new argument called `experimental_write_callbacks`.
-    These are callbacks that will be executed after a saving event finishes
-    writing the checkpoint file.
-* Add an option `disable_eager_executer_streaming_enqueue` to
-  `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior
-  around parallel remote function invocations; when set to `True`, the eager
-  runtime will be allowed to execute multiple function invocations in parallel.
+    * It now takes in a new argument called `experimental_write_callbacks`. These are callbacks that will be executed after a saving event finishes writing the checkpoint file.
+* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel.
 * `tf.constant_initializer`
-    * It now takes a new argument called `support_partition`.
-    If True, constant_initializers can create sharded variables.
-    This is disabled by default, similar to existing behavior.
+    * It now takes a new argument called `support_partition`. If True, constant_initializers can create sharded variables. This is disabled by default similar to existing behavior.
 
 * `tf.lite`
     * Added support for `stablehlo.scatter`.
@@ -177,7 +172,7 @@
 
 This release contains contributions from many people at Google, as well as:
 
-<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
+Aiden Grossman, Akash Patel, Akhil Goel, Alexander Pivovarov, Andrew Goodbody, Ayan Moitra, Ben Barsdell, Ben Olson, Bhavani Subramanian, Boian Petkantchin, Bruce Lai, Chao Chen, Christian Steinmeyer, cjflan, David Korczynski, Donghak Park, Dragan Mladjenovic, Eli Kobrin, Fadi Arafeh, Feiyue Chen, Frédéric Bastien, guozhong.zhuang, halseycamilla, Harshavardhan Bellamkonda, James Ward, jameshollyer, Jane Liu, johnnkp, jswag180, justkw, Kanvi Khanna, Keith Smiley, Koan-Sin Tan, Kulin Seth, Kun-Lu, kushanam, Lu Teng, mdfaijul, Mehdi Drissi, mgokulkrish, mraunak, Mustafa Uzun, Namrata Bhave, Pavel Emeliyanenko, pemeliya, Peng Sun, Philipp Hack, Pratik Joshi, Rahul Batra, Raunak, redwrasse, Saoirse Stewart, SaoirseARM, seanshpark, Shanbin Ke, Spenser Bauman, Surya, sushreebarsa, Tai Ly, Thibaut Goetghebuer-Planchon, tilakrayal, Tirumalesh, Tj Xu, Vladislav, weihanmines, Wen Chen, wenchenvincent, wenscarl, William Muir, Zhoulong, Jiang
 
 # Release 2.14.0
 

WORKSPACE

@@ -14,11 +14,15 @@ http_archive(
 
 http_archive(
     name = "rules_python",
-    sha256 = "5868e73107a8e85d8f323806e60cad7283f34b32163ea6ff1020cf27abef6036",
-    strip_prefix = "rules_python-0.25.0",
-    url = "https://github.com/bazelbuild/rules_python/releases/download/0.25.0/rules_python-0.25.0.tar.gz",
+    sha256 = "9d04041ac92a0985e344235f5d946f71ac543f1b1565f2cdbc9a2aaee8adf55b",
+    strip_prefix = "rules_python-0.26.0",
+    url = "https://github.com/bazelbuild/rules_python/releases/download/0.26.0/rules_python-0.26.0.tar.gz",
 )
 
+load("@rules_python//python:repositories.bzl", "py_repositories")
+
+py_repositories()
+
 load("@rules_python//python:repositories.bzl", "python_register_toolchains")
 load(
     "//tensorflow/tools/toolchains/python:python_repo.bzl",

ci/official/containers/linux_arm64/Dockerfile

@@ -78,4 +78,7 @@ COPY devel.requirements.txt /devel.requirements.txt
 COPY setup.python.sh /setup.python.sh
 RUN /setup.python.sh python3.9 devel.requirements.txt
 RUN /setup.python.sh python3.10 devel.requirements.txt
-RUN /setup.python.sh python3.11 devel.requirements.txt
+RUN /setup.python.sh python3.11 devel.requirements.txt
+# "python3" commands by default run under 3.10
+RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 1
+# RUN /setup.python.sh python3.12 devel.requirements.txt

ci/official/containers/linux_arm64/devel.usertools/wheel_verification.bats

@@ -69,7 +69,7 @@ teardown_file() {
 # Is this still useful?
 @test "TensorFlow has Keras" {
     source /tf/venv/bin/activate
-    python3 -c 'import sys; import tensorflow as tf; sys.exit(0 if "_v2.keras" in tf.keras.__name__ else 1)'
+    python3 -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
 }
 
 # Is this still useful?

ci/official/envs/ci_default

@@ -14,6 +14,8 @@ TFCI_LIB_SUFFIX=
 TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=
 TFCI_NVIDIA_SMI_ENABLE=
 TFCI_OUTPUT_DIR=build_output
+TFCI_LIBTPU_DOWNLOAD_ENABLE=0
+TFCI_LIBTPU_DOWNLOAD_URL=
 TFCI_UPLOAD_LIB_ENABLE=
 TFCI_UPLOAD_LIB_LATEST_ENABLE=
 TFCI_UPLOAD_LIB_LATEST_URI=

ci/official/envs/nightly_linux_arm64_cpu_py310

@@ -1,7 +1,7 @@
 source ci/official/envs/ci_default
 source ci/official/envs/ci_nightly_uploads
-TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
 TFCI_BAZEL_COMMON_ARGS=(--config release_arm64_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.10)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
 TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-latest-multi-python
 TFCI_DOCKER_REBUILD_ARGS=(--target=tf ci/official/containers/linux_arm64)

ci/official/envs/nightly_linux_arm64_cpu_py311

@@ -0,0 +1,8 @@
+source ci/official/envs/ci_default
+source ci/official/envs/ci_nightly_uploads
+TFCI_BAZEL_COMMON_ARGS=(--config release_arm64_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.11)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
+TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
+TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-latest-multi-python
+TFCI_DOCKER_REBUILD_ARGS=(--target=tf ci/official/containers/linux_arm64)
+TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=1

ci/official/envs/nightly_linux_arm64_cpu_py39

@@ -0,0 +1,8 @@
+source ci/official/envs/ci_default
+source ci/official/envs/ci_nightly_uploads
+TFCI_BAZEL_COMMON_ARGS=(--config release_arm64_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.9)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
+TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
+TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-latest-multi-python
+TFCI_DOCKER_REBUILD_ARGS=(--target=tf ci/official/containers/linux_arm64)
+TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=1

ci/official/envs/nightly_linux_x86_cpu_py310

@@ -1,7 +1,7 @@
 source ci/official/envs/ci_default
 source ci/official/envs/ci_nightly_uploads
-TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BAZEL_COMMON_ARGS=(--config release_cpu_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.10)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
 TFCI_DOCKER_IMAGE=tensorflow/build:latest-python3.10
 TFCI_DOCKER_REBUILD_ARGS=(--build-arg PYTHON_VERSION=3.10 --target=devel tools/tf_sig_build_dockerfiles)

ci/official/envs/nightly_linux_x86_cpu_py311

@@ -1,7 +1,7 @@
 source ci/official/envs/ci_default
 source ci/official/envs/ci_nightly_uploads
-TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BAZEL_COMMON_ARGS=(--config release_cpu_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.11)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
 TFCI_DOCKER_IMAGE=tensorflow/build:latest-python3.11
 TFCI_DOCKER_REBUILD_ARGS=(--build-arg PYTHON_VERSION=3.11 --target=devel tools/tf_sig_build_dockerfiles)

ci/official/envs/nightly_linux_x86_cpu_py39

@@ -1,7 +1,7 @@
 source ci/official/envs/ci_default
 source ci/official/envs/ci_nightly_uploads
-TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BAZEL_COMMON_ARGS=(--config release_cpu_linux --config tf_public_cache_push --config resultstore --repo_env=TF_PYTHON_VERSION=3.9)
+TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
 TFCI_BUILD_PIP_PACKAGE_ARGS=(--cpu --nightly_flag)
 TFCI_DOCKER_IMAGE=tensorflow/build:latest-python3.9
 TFCI_DOCKER_REBUILD_ARGS=(--build-arg PYTHON_VERSION=3.9 --target=devel tools/tf_sig_build_dockerfiles)