{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

"""

import logging
import unittest
import pkg_resources

logging.basicConfig(level=logging.INFO)


class ImportApiPackagesTest(unittest.TestCase):
  """ImportApiPackagesTest class. See description at the top of the file."""

  def setUp(self):
    def _get_api_packages_v2():
      api_packages_path = pkg_resources.resource_filename(
          "tensorflow", "_api/v2/api_packages.txt"
      )

  };
  explicit AbstractOperation(AbstractOperationKind kind) : kind_(kind) {}
  virtual ~AbstractOperation() {}

 public:
  AbstractOperationKind getKind() const { return kind_; }

  // Release any underlying resources, including the interface object.
  //
  // WARNING: The destructor of this class is marked as protected to disallow
  // clients from directly destroying this object since it may manage it's own

implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but
we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

        "//tensorflow/core:framework",
        "//tensorflow/core/platform:errors",
    ],
)

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

    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

filegroup(
    name = "sources",
    srcs = [
        ":device_sources",
        ":lib_sources",
    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

cc_library(
    name = "parallel_device",
    srcs = [":device_sources"],
    hdrs = [":device_headers"],
    visibility = ["//visibility:private"],
    deps = [

# limitations under the License.
# ==============================================================================
# Variables containing version strings extracted from the canonical sources:
# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a

  explicit AbstractContext(AbstractContextKind kind) : kind_(kind) {}
  virtual ~AbstractContext() {}

 public:
  AbstractContextKind getKind() const { return kind_; }

  // Release any underlying resources, including the interface object.
  //
  // WARNING: The destructor of this class is marked as protected to disallow
  // clients from directly destroying this object since it may manage its own

# almost all of the same cache layers
export DOCKER_BUILDKIT=1
for target in jax tf; do
  IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG"
  docker pull "$IMAGE" || true
  # Due to some flakiness of resources pulled in the build, allow the docker
  # command to reattempt build a few times in the case of failure (b/302558736)
  set +e
  for i in $(seq 1 5)
  do
    docker build \

# LLVM/Clang: https://apt.llvm.org/
apt-key adv --fetch-keys https://apt.llvm.org/llvm-snapshot.gpg.key

# Set up custom sources
cat >/etc/apt/sources.list.d/custom.list <<SOURCES
# More Python versions: Deadsnakes
deb http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main
deb-src http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main

# LLVM/Clang 17 repository