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ci/official/utilities/generate_index_html.sh

# limitations under the License.
# ==============================================================================

# Generates a handy index.html with a bunch of Kokoro links for GitHub
# presubmits.
# Usage: generate_index_html.sh /path/to/output/index.html

cat > "$1" <<EOF
<html>
<head>
<title>$(basename "$KOKORO_JOB_NAME")</title>
</head>
<body>
<h1>TensorFlow Job Logs and Links</h1>
<h2>Job Details</h2>
<ul>

Shell Script

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc

# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/cuda.packages.txt

# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn8=8.9.6.50-1+cuda12.2
libcudnn8-dev=8.9.6.50-1+cuda12.2

# This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image.
# For now it ensures that we install at least version 12.3.107 of PTXAS,
# since 12.3.103 has a bug.

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github.com/tensorflow/tensorflow

ci/official/envs/linux_arm64

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"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1
TFCI_WHL_AUDIT_PLAT=manylinux2014_aarch64
TFCI_WHL_BAZEL_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=240M

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc

# > 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.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

# Disable clang extension that rejects type definitions within offsetof. 
# This was added in clang-16 by https://reviews.llvm.org/D133574.

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github.com/tensorflow/tensorflow

ci/official/pycpp.sh

fi

# Note: the profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

Shell Script

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github.com/tensorflow/tensorflow

ci/official/envs/linux_x86_tpu

TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M

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github.com/tensorflow/tensorflow

ci/official/envs/macos_arm64

TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_macos_arm64"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_arm64
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-darwin-arm64"
TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1
TFCI_MACOS_BAZEL_TEST_DIR_PATH="/Volumes/BuildData/bazel_output"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_BAZEL_TEST_ENABLE=1

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github.com/tensorflow/tensorflow

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

            echo "The wheel's name is in an unknown format."
            exit 1
            ;;
    esac
    # >&3 forces output in bats even if the test passes. See
    # https://bats-core.readthedocs.io/en/stable/writing-tests.html#printing-to-the-terminal
    echo "# Size of $TF_WHEEL is $WHEEL_MEGABYTES / $LARGEST_OK_SIZE megabytes." >&3
    test "$WHEEL_MEGABYTES" -le "$LARGEST_OK_SIZE"
}

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github.com/tensorflow/tensorflow

SECURITY.md

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that
come with the compiler are not designed to be used with untrusted data and
should be used with caution when working with untrusted models.

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