"""

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"
      )

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).

for machine learning. It has a comprehensive, flexible ecosystem of
[tools](https://www.tensorflow.org/resources/tools),
[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
[community](https://www.tensorflow.org/community) resources that lets
researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

// LINT.IfChange
typedef struct TF_FilesystemOps {
  /// Acquires all resources used by the filesystem.
  ///
  /// This operation must be provided. See "REQUIRED OPERATIONS" above.
  void (*init)(TF_Filesystem* filesystem, TF_Status* status);

  /// Releases all resources used by the filesystem
  ///
  /// NOTE: TensorFlow does not unload DSOs. Thus, the only way a filesystem

        "//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

            static_cast<TF_Code>(tensorflow::error::PERMISSION_DENIED));
  EXPECT_EQ(TF_UNAUTHENTICATED,
            static_cast<TF_Code>(tensorflow::error::UNAUTHENTICATED));
  EXPECT_EQ(TF_RESOURCE_EXHAUSTED,
            static_cast<TF_Code>(tensorflow::error::RESOURCE_EXHAUSTED));
  EXPECT_EQ(TF_FAILED_PRECONDITION,
            static_cast<TF_Code>(tensorflow::error::FAILED_PRECONDITION));

  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);
}
BENCHMARK(BM_ExecuteFunction)->Arg(0)->Arg(1);

TEST(CAPI, Variables) {
  // Variables use resource handles, so this is really a test for resource
  // tensor handling.
  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);

                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);