};

void TF_CreateDir(const char* dirname, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(
      status, ::tensorflow::Env::Default()->CreateDir(dirname));
}

void TF_DeleteDir(const char* dirname, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(
      status, ::tensorflow::Env::Default()->DeleteDir(dirname));
}

  tensorflow::gtl::FlatSet<int64_t> sources_set(source_tensor_ids.begin(),
                                                source_tensor_ids.end());
  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;
  for (int i = 0; i < target_tensor_ids.size(); ++i) {
    int64_t target_id = target_tensor_ids[i];
    if (sources_set.find(target_id) != sources_set.end()) {
      auto tensor = targets[i];

  TF_Output add_inputs[2] = {{l, 0}, {r, 0}};
  TF_AddInputList(desc, add_inputs, 2);
  TF_AddControlInput(desc, ctrl_op);
  return TF_FinishOperation(desc, s);
}

// If `op_device` is non-empty, set the created op on that device.
void BinaryOpHelper(const char* op_name, TF_Operation* l, TF_Operation* r,
                    TF_Graph* graph, TF_Status* s, const char* name,

  EXPECT_EQ("test/counter",
            metrics->point_set_map.at("test/counter")->metric_name);
  EXPECT_EQ(
      1, metrics->point_set_map.at("test/counter")->points.at(0)->int64_value);

  TFE_MonitoringCounterCellIncrementBy(cell, 5);
  EXPECT_EQ(TFE_MonitoringCounterCellValue(cell), 6);
  metrics = collection_registry->CollectMetrics(options);
  EXPECT_EQ(
      6, metrics->point_set_map.at("test/counter")->points.at(0)->int64_value);

    if (!v2_reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, v2_reader_->status());
      return;
    }
    auto result = BuildV2VarMaps();
    var_to_shape_map_.swap(result.first);
    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;

  tensorflow::ServerDef single_host_server_def;
  single_host_server_def.set_job_name("worker");
  single_host_server_def.set_protocol(cluster_server_def.protocol());
  single_host_server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def =
      single_host_server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name("client");

  // Add a client.

  ops_->set_filesystem_configuration(filesystem_.get(), &option, 1,
                                     plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

Status ModularFileSystem::SetOption(const std::string& name,
                                    const std::vector<int64_t>& values) {
  if (ops_->set_filesystem_configuration == nullptr) {

  // max_age of 0 means nothing will be cached.
  tf_gcs_filesystem::ExpiringLRUCache<int> cache1(0, 4);
  cache1.Insert("a", 1);
  int value = 0;
  EXPECT_FALSE(cache1.Lookup("a", &value));
  // Now set max_age = 1 and verify the LRU eviction logic.
  tf_gcs_filesystem::ExpiringLRUCache<int> cache2(1, 4);
  cache2.Insert("a", 1);
  cache2.Insert("b", 2);
  cache2.Insert("c", 3);
  cache2.Insert("d", 4);

  EXPECT_EQ(-1, num_dims);

  // Set the shape to be unknown, expect no change.
  TF_GraphSetTensorShape(graph, feed_out_0, /*dims=*/nullptr, -1, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  num_dims = TF_GraphGetTensorNumDims(graph, feed_out_0, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(-1, num_dims);

  // Set the shape to be 2 x Unknown
  int64_t dims[] = {2, -1};

                             << ", offset = " << offset << ", n = " << n;
      }
    }
  }
}

TEST(RamFileBlockCacheTest, CacheHits) {
  const size_t block_size = 16;
  std::set<size_t> calls;
  auto fetcher = [&calls, block_size](const string& filename, size_t offset,
                                      size_t n, char* buffer,
                                      TF_Status* status) -> int64_t {