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ci/official/containers/linux_arm64/devel.requirements.txt
portpicker==1.6.0 # For wheel verification, and uploading auditwheel ~= 5.4.0
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ci/official/containers/linux_arm64/jax.requirements.txt
# JAX requirements, passed into container by defining the ARG # REQUIREMENTS_FILE=jax.requirements.txt setuptools wheel cloudpickle colorama>=0.4.4 matplotlib pillow>=9.1.0 rich absl-py portpicker six opt-einsum auditwheel typing_extensions importlib_metadata>=4.6 numpy==1.26.0;python_version=="3.12" numpy==1.23.4;python_version=="3.11" numpy==1.22.4;python_version<"3.11" scipy==1.11.2;python_version=="3.12"
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ci/official/envs/linux_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=tensorflow/build:2.16-python${TFCI_PYTHON_VERSION} TFCI_DOCKER_PULL_ENABLE=1
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ci/official/envs/macos_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_macos_x86" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_x86 TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-x86_64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/System/Volumes/Data/bazel_output" TFCI_MACOS_INSTALL_BAZELISK_ENABLE=1
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ci/official/envs/linux_arm64
# Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1 TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64"
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# odd to attempt to validate the quality of the pip package. The wheel is # installed into a virtual environment, and then that venv is used to run all # bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which # drops all the bazel dependencies for each py_test; this makes all the tests # use the wheel's TensorFlow installation instead of the one made available
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requirements_lock_3_12.txt
werkzeug==3.0.1 \ --hash=sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc \ --hash=sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10 # via tb-nightly wheel==0.41.3 \ --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \ --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841 # via # -r requirements.in
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requirements_lock_3_9.txt
werkzeug==3.0.1 \ --hash=sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc \ --hash=sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10 # via tb-nightly wheel==0.41.3 \ --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \ --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841 # via # -r requirements.in
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requirements_lock_3_10.txt
werkzeug==3.0.1 \ --hash=sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc \ --hash=sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10 # via tb-nightly wheel==0.41.3 \ --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \ --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841 # via # -r requirements.in
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docs/en/docs/release-notes.md
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