issue in TensorFlow Lite that is not about Converters, Play Services or Ops
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markdown attributes: value: | Please make sure that this is a bug. As per our

        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:span",
        "@com_google_absl//absl/types:variant",
    ],
)

tf_cc_test(
    name = "parallel_device_lib_test",
    srcs = ["parallel_device_lib_test.cc"],
    deps = [
        ":parallel_device_lib",

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files
    if [[ "$(git rev-parse --abbrev-ref HEAD)" == "pull_branch" ]]; then
        # TF's CI runs 'git fetch origin "pull/PR#/merge:pull_branch"'
        # To get the as-merged branch during the CI tests

        ":tf_file_statistics",
        ":tf_status",
        ":tf_status_helper",
        "//tensorflow/core/platform:env",
        "//tensorflow/core/platform:path",
        "//tensorflow/core/platform:types",
    ],
)

cc_library(
    name = "kernels_hdrs",
    hdrs = [
        "kernels.h",
        "kernels_experimental.h",
    ],
    visibility = ["//tensorflow:internal"],
    deps = [

            "//tensorflow/core/profiler/lib:traceme",
            "@com_google_absl//absl/algorithm:container",
            "@com_google_absl//absl/types:span",
            "@com_google_absl//absl/types:variant",
        ],
    }) + [
        ":abstract_tensor_handle",
        "//tensorflow/c:c_api_macros_hdrs",
        "//tensorflow/core:gpu_runtime",

which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily

      transformation or translation of a Source form, including but
      not limited to compiled object code, generated documentation,
      and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work

* Making the `tf.function` type system fully available:

    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.

        "//third_party/py/courier/...",
        "//third_party/py/tensorfn/...",
    ],
)

# Packages that use private types symbols, until they are exported.
# TODO(b/154650521) Remove.
# If this is modified, then copy.bara.sky must also be modified.
package_group(name = "types_allowlist")

# Packages that use StructuredTensors.
# TODO(b/159007891) Remove this package once StructuredTensor is exported.

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.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.