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ci/official/containers/linux_arm64/Dockerfile
COPY cuda.packages.txt /cuda.packages.txt RUN /setup.sources.sh && /setup.packages.sh /devel.packages.txt # Install various tools. # - bats: bash unit testing framework # NOTE: v1.6.0 seems to have a bug that made "git" in setup_file break # - bazelisk: always use the correct bazel version # - buildifier: clean bazel build deps # - buildozer: clean bazel build deps
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# 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 # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. #
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# 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 # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. #
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ci/official/README.md
# First, set your TFCI variable to choose the environment settings. # TFCI is a comma-separated list of filenames from the envs directory, which # are all settings for the scripts. TF's CI jobs are all made of a combination # of these env files. # # If you've clicked on a test result from our CI (via a dashboard or GitHub link), # click to "Invocation Details" and find BUILD_CONFIG, which will contain a TFCI
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tensorflow/c/eager/gradients.h
absl::Span<AbstractTensorHandle*> grad_inputs) = 0; virtual ~GradientFunction() {} }; // Metadata from the forward operation that is made available to the // gradient registerer to instantiate a GradientFunction. struct ForwardOperation { public: string op_name; std::vector<AbstractTensorHandle*> inputs; std::vector<AbstractTensorHandle*> outputs;
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