http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [
        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
        "https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
    ],
)

http_archive(
    name = "rules_python",

# - buildifier: clean bazel build deps
# - buildozer: clean bazel build deps
RUN git clone --branch v1.7.0 https://github.com/bats-core/bats-core.git && bats-core/install.sh /usr/local && rm -rf bats-core
RUN wget --retry-connrefused --waitretry=1 --read-timeout=20 --timeout=15 --tries=5 https://github.com/bazelbuild/bazelisk/releases/download/v1.12.0/bazelisk-linux-arm64 -O /usr/local/bin/bazel && chmod +x /usr/local/bin/bazel

  cat > $BATS_TEST_TMPDIR/allowed_to_be_missing <<EOF
@absl_py//absl
@bazel_tools//platforms
@bazel_tools//third_party/
@bazel_tools//tools
@local
@com_google_absl//absl
@org_tensorflow//
@com_github_googlecloudplatform_google_cloud_cpp//google
@com_github_grpc_grpc//src/compiler
@platforms//os
@ruy//
EOF

  # grep patterns for targets which are allowed to be extra licenses

# 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.

    harassment or another code of conduct violation, report it.

## Reporting Violations

# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
# Change the value of CACHEBUSTER when upgrading the toolchain, or when testing
# different compilation methods. E.g. for a PR to test a new CUDA version, set

        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:variant",
    ],
)

cc_library(
    name = "parallel_device_lib",
    srcs = [":lib_sources"],
    hdrs = [":lib_headers"],

[GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md),we
only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub.

-   type: markdown
    attributes:
      value: |

[requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater)
tool using the path to this wheel file.

### Hermetic Python

For details about hermetic Python and setting its toolchain version, see
[requirements updater readme](https://github.com/tensorflow/tensorflow/blob/master/ci/official/requirements_updater/README.md)

        "//tensorflow/c/eager:c_api_unified_internal",
        "//tensorflow/c/eager:tracing_utils",
        "//tensorflow/core:framework",
        "//tensorflow/core/platform:errors",
        "@com_google_absl//absl/types:span",
    ],
)

cc_library(
    name = "io_ops",
    srcs = [
        "io_ops.cc",
    ],
    hdrs = [
        "io_ops.h",
    ],
    visibility = [