memset(buffer, 'x', n);
    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  const uint32 block_count = 256;
  tf_gcs_filesystem::RamFileBlockCache cache(
      block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  out.resize(block_count, 0);
  // The cache has space for `block_count` blocks. The loop with i = 0 should
  // fill the cache, and the loop with i = 1 should be all cache hits. The

      new TensorSliceReader::VarToDataTypeMap);
  v2_reader_->Seek(kHeaderEntryKey);
  for (v2_reader_->Next(); v2_reader_->Valid(); v2_reader_->Next()) {
    if (filtered_keys.count(string(v2_reader_->key())) > 0) continue;
    CHECK(entry.ParseFromArray(v2_reader_->value().data(),
                               v2_reader_->value().size()))
        << entry.InitializationErrorString();

      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In sync mode, forwarding can't really happen since the client code will
      // have a reference count on the input tensor while the kernel is being
      // executed and thus it cannot be re-used for the return tensor.
      EXPECT_NE(orig_ptr, TF_TensorData(t));
    }
  }

    if (edge->src_output() == oper_out.index) {
      if (count < max_consumers) {
        consumers[count] = {ToOperation(edge->dst()), edge->dst_input()};
      }
      ++count;
    }
  }
  return count;
}

int TF_OperationNumControlInputs(TF_Operation* oper) {
  int count = 0;
  for (const auto* edge : oper->node.in_edges()) {
    if (edge->IsControlEdge() && !edge->src()->IsSource()) {

    "@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

  return *factories;
}

static tracing::FactoryFunction default_factory;

void RegisterTracingEngineFactory(const string& name, FactoryFunction factory) {
  assert((!GetFactories().count(name)) ||
         (GetFactories()[name] == factory) &&
             "Duplicate tracing factory registration");
  GetFactories()[name] = factory;
}

Status SetDefaultTracingEngine(const char* name) {

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;
}

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