}
        }
      }
      auto usage_count_it = state.tensor_usage_counts.find(id);
      if (usage_count_it == state.tensor_usage_counts.end()) {
        VLOG(1) << "Tensor " << id << " not used";
        continue;
      }
      usage_count_it->second--;
      if (usage_count_it->second > 0) {
        VLOG(1) << "Tensor " << id << " usage count " << usage_count_it->second;
        continue;
      }

    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cuda_driver + "\
    "@local_config_cuda//cuda:cudnn + "\
    "@local_config_cuda//cuda:curand + "\
    "@local_config_cuda//cuda:cusolver + "\
    "@local_config_tensorrt//:tensorrt)" --keep_going > $BATS_TEST_TMPDIR/out

  cat <<EOF
There was a path found connecting //tensorflow/tools/pip_package:wheel

  # ROCm / CUDA are mutually exclusive.
  # At most 1 GPU platform can be configured.
  gpu_platform_count = 0
  if environ_cp.get('TF_NEED_ROCM') == '1':
    gpu_platform_count += 1
  if environ_cp.get('TF_NEED_CUDA') == '1':
    gpu_platform_count += 1
  if gpu_platform_count >= 2:
    raise UserInputError('CUDA / ROCm are mututally exclusive. '

// a) ConfigProto.optimizer_options.global_jit_level is set to ON_1 if
// `enable_xla_compilation` is non-zero, and OFF otherwise.
// b) ConfigProto.gpu_options.allow_growth is set to `gpu_memory_allow_growth`.
// c) ConfigProto.device_count is set to `num_cpu_devices`.
TF_CAPI_EXPORT extern TF_Buffer* TF_CreateConfig(
    unsigned char enable_xla_compilation, unsigned char gpu_memory_allow_growth,
    unsigned int num_cpu_devices);

  }

  auto* gpu_options = config.mutable_gpu_options();
  gpu_options->set_allow_growth(gpu_memory_allow_growth);

  (*config.mutable_device_count())["CPU"] = num_cpu_devices;

  // TODO(b/113217601): This is needed for EagerContext::runner_ to use a
  // threadpool, so that we avoid the possibility of running the runner_ in the

void TF_DeleteRecursively(const char* dirname, int64_t* undeleted_file_count,
                          int64_t* undeleted_dir_count, TF_Status* status) {
  ::int64_t f, d;

  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(
      status, ::tensorflow::Env::Default()->DeleteRecursively(dirname, &f, &d));
  *undeleted_file_count = f;
  *undeleted_dir_count = d;
}

  /// that no entry is ever placed in the cache.
  const uint64_t max_age_;

  /// The maximum number of entries in the cache. A value of 0 means there is no
  /// limit on entry count.
  const size_t max_entries_;

  /// The callback to read timestamps.
  std::function<uint64_t()> timer_seconds_;

  /// Guards access to the cache and the LRU list.
  absl::Mutex mu_;

typedef struct TFE_MonitoringBuckets TFE_MonitoringBuckets;
TF_CAPI_EXPORT extern TFE_MonitoringBuckets*
TFE_MonitoringNewExponentialBuckets(double scale, double growth_factor,
                                    int bucket_count);
TF_CAPI_EXPORT extern void TFE_MonitoringDeleteBuckets(
    TFE_MonitoringBuckets* buckets);

// APIs for Sampler without label.
typedef struct TFE_MonitoringSampler0 TFE_MonitoringSampler0;

# limitations under the License.
# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then

# limitations under the License.
# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then