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  1. CONTRIBUTING.md

    ***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.
    
    ### Contributing code
    
    If you have improvements to TensorFlow, send us your pull requests! For those
    just getting started, GitHub has a
    [how-to](https://help.github.com/articles/using-pull-requests/).
    
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  2. ci/official/utilities/code_check_changed_files.bats

    }
    
    @test "API compatibility test passes, ensuring no unexpected changes to the TF API" {
        bazel test $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/api/tests:api_compatibility_test
        echo "You have to re-generate the TF API goldens and have the API changes reviewed."
        echo "Look at the instructions for ':api_compatibility_test -- --update_goldens=True'"
    }
    
    teardown_file() {
        bazel shutdown
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  3. ci/official/envs/linux_arm64

    TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=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
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  4. CODE_OF_CONDUCT.md

    Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
    
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  5. ISSUES.md

        a documentation issue (for small doc fixes please send a PR instead).
    1.  Make sure the Issue Template is filled out.
    1.  The issue should be related to the repo it is created in.
    
    **Here's why we have this policy:** We want to focus on the work that benefits
    the whole community, e.g., fixing bugs and adding features. Individual support
    should be sought on Stack Overflow or other non-GitHub channels. It helps us to
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  6. 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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  7. ci/official/README.md

    #   Non-Googlers should replace "nightly_upload" or "rbe" with
    #   "public_cache,disk_cache".
    #   Googlers should replace "nightly_upload" with "public_cache,disk_cache" or
    #   "rbe", if you have set up your system to use RBE (see further below).
    #
    # Here is how to choose your TFCI value:
    # 1. A Python version must come first, because other scripts reference it.
    #      Ex. py39  -- Python 3.9
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  8. SECURITY.md

    in taking those formats, modifying them, and/or converting them to intermediate
    formats that can be processed by TensorFlow.
    
    These modifications and conversions are handled by a variety of libraries that
    have different security properties and provide different levels of confidence
    when dealing with untrusted data. Based on the security history of these
    libraries we consider that it is safe to work with untrusted inputs for PNG,
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  9. ci/official/envs/rbe

    # These flags share the user's gcloud credentials with the container, so that bazel
    # inside the container can authenticate. Note: TF's CI does not have any credential
    # stored here.
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  10. ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc

    build --linkopt="-Wl,--undefined-version"
    
    # Prevent double-compilation of some TF code, ref. b/183279666 (internal)
    # > TF's gen_api_init_files has a genrule to run the core TensorFlow code
    # > on the host machine. If we don't have --distinct_host_configuration=false,
    # > the core TensorFlow code will be built once for the host and once for the
    # > target platform.
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