const string gpu_device_name = GPUDeviceName(sess);
  TF_DeleteSession(sess, s);
  CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  return gpu_device_name;
}

TEST(CAPI, Version) { EXPECT_STRNE("", TF_Version()); }

TEST(CAPI, Status) {
  TF_Status* s = TF_NewStatus();
  EXPECT_EQ(TF_OK, TF_GetCode(s));
  EXPECT_EQ(string(), TF_Message(s));
  TF_SetStatus(s, TF_CANCELLED, "cancel");

        # "//tools/cpp:asan_build": [
        # "-Wl,--version-script,$(location //tensorflow/c:version_script.lds)",
        # ],
        # "//tools/cpp:hwasan_build": [
        # "-Wl,--version-script,$(location //tensorflow/c:version_script.lds)",
        # ],
        # "//tools/cpp:msan_build": [
        # "-Wl,--version-script,$(location //tensorflow/c:version_script.lds)",
        # ],

  curr_version_split = curr_version.lower().split('clang version ')
  if len(curr_version_split) > 1:
    curr_version = curr_version_split[1].split()[0]

  curr_version_int = convert_version_to_int(curr_version)
  # Check if current clang version can be detected properly.
  if not curr_version_int:
    print('WARNING: current clang installation is not a release version.\n')
    return None

build:cuda_clang --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_60,sm_70,sm_80,sm_89,compute_90"

# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
build:cuda_clang_official --config=cuda_clang
build:cuda_clang_official --action_env=TF_CUDA_VERSION="12"
build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"
build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3"