setup_file() {
    bazel version  # Start the bazel server

    # Fixes "fatal: detected dubious ownership in repository" for Docker.
    git config --system --add safe.directory '*'
    git config --system protocol.file.allow always

    # 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

cc_library(
    name = "parallel_device_lib",
    srcs = [":lib_sources"],
    hdrs = [":lib_headers"],
    visibility = ["//tensorflow:internal"],
    deps = [
        "//tensorflow/c:c_api",
        "//tensorflow/c:safe_ptr",
        "//tensorflow/c:tf_status_internal",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_cancellation_manager_internal",

    licenses = ["notice"],
)

filegroup(
    name = "safe_ptr_hdr",
    srcs = ["safe_ptr.h"],
    visibility = [
        "//tensorflow:internal",
    ],
)

cc_library(
    name = "safe_ptr",
    srcs = [
        "safe_ptr.cc",
        "//tensorflow/c/eager:headers",
    ],
    hdrs = ["safe_ptr.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [

whether these uses were recommended or considered safe, or where we recommend
some form of isolation when dealing with untrusted data. As a result, this
document also outlines what issues we consider as TensorFlow security
vulnerabilities.

We recognize issues as vulnerabilities only when they occur in scenarios that we
outline as safe; issues that have a security impact only when TensorFlow is used

      the brackets!)  The text should be enclosed in the appropriate
      comment syntax for the file format. We also recommend that a
      file or class name and description of purpose be included on the
      same "printed page" as the copyright notice for easier
      identification within third-party archives.

   Copyright [yyyy] [name of copyright owner]

   Licensed under the Apache License, Version 2.0 (the "License");

        small increase in memory usage due to buffering. To enable this
        behavior, set `inject_prefetch=True` in
        `tf.data.experimental.OptimizationOptions`.
    *   Added a new value to `tf.data.Options.autotune.autotune_algorithm`:
        `STAGE_BASED`. If the autotune algorithm is set to `STAGE_BASED`, then
        it runs a new algorithm that can get the same performance with lower
        CPU/memory usage.

# REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from
# libtensorflow_framework.so), and pywrap_tensorflow can then use these
# ops. Since other languages use the same libtensorflow_framework.so, op
# libraries are language agnostic.
#
# This shared object is not used unless framework_shared_object=true (set in the