// before the function execution starts.
  TFE_ContextAsyncWait(ctx, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Pack 3 variable handles into one TFE_TensorHandle.
  // When remote is false, function device is placed on task0. Handle types are
  // REMOTE, REMOTE, LOCAL on task0. When remote is true, function device is
  // placed on task1, Handle types are LOCAL, REMOTE, LOCAL on task1.
  int num_replicas = 3;

    stack_traces[n->name()] = n->GetStackTrace();
  }

  TF_Function* tf_function = new TF_Function();
  tf_function->record = new tensorflow::FunctionRecord(
      std::move(fdef), std::move(stack_traces), false);

  return tf_function;
}

TF_Function* TF_GraphToFunction(const TF_Graph* fn_body, const char* fn_name,
                                unsigned char append_hash_to_fn_name,

  if (TF_GetCode(status) != TF_OK) return false;
  if (is_folder) return true;

  bool is_object = ObjectExists(gcs_file, path, bucket, object, status);
  if (TF_GetCode(status) != TF_OK) return false;
  if (is_object) {
    TF_SetStatus(
        status, TF_FAILED_PRECONDITION,
        absl::StrCat("The specified path ", path, " is not a directory.")
            .c_str());
    return false;
  }

                                /*transpose_a = */ false,
                                /*transpose_b = */ false, name_grad_A.c_str()));

      TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, A.get(), &matmul_B_output,
                                /*transpose_a = */ true,
                                /*transpose_b = */ false, name_grad_B.c_str()));

    } else if (t_a && !t_b) {

  TFE_ContextSetServerDefWithTimeoutAndRetries(
      ctx, keep_alive_secs, proto, proto_len, /*init_timeout_in_ms=*/0,
      /*retries=*/0, status, /*clear_existing_contexts=*/false);
}

// Set server def with timeout.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,

      *device_name = dev_name;
      LOG(INFO) << "Found " << device_type << " device " << *device_name;
      TF_DeleteDeviceList(devices);
      return true;
    }
  }
  TF_DeleteDeviceList(devices);
  return false;
}

tensorflow::ServerDef GetServerDef(const string& job_name, int num_tasks) {
  tensorflow::ServerDef server_def;
  server_def.set_protocol("grpc");
  server_def.set_job_name(job_name);

#endif  // !defined(PLATFORM_WINDOWS)
}

void DefineFunction(const char* name, TF_Function** func,
                    const char* description = nullptr,
                    bool append_hash = false) {
  std::unique_ptr<TF_Graph, decltype(&TF_DeleteGraph)> func_graph(
      TF_NewGraph(), TF_DeleteGraph);
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> s(TF_NewStatus(),

void TFE_ContextEnableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(true);
}

void TFE_ContextDisableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(false);
}

uint64_t TFE_GetContextId(TFE_Context* ctx) {
  tensorflow::EagerContext* context =
      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));
  return context->GetContextId();
}

  TFE_DeleteContextOptions(opts);
  TFE_ContextAddFunction(ctx, fn, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TF_DeleteFunction(fn);

  for (bool async : {false, true, false}) {
    TFE_Executor* old_executor = TFE_ContextGetExecutorForThread(ctx);
    TFE_Executor* executor = TFE_NewExecutor(
        /*is_async=*/async, /*enable_streaming_enqueue=*/true,

  tf_gcs_filesystem::RamFileBlockCache cache3(0, 32, 0, fetcher);
  tf_gcs_filesystem::RamFileBlockCache cache4(16, 32, 0, fetcher);

  EXPECT_FALSE(cache1.IsCacheEnabled());
  EXPECT_FALSE(cache2.IsCacheEnabled());
  EXPECT_FALSE(cache3.IsCacheEnabled());
  EXPECT_TRUE(cache4.IsCacheEnabled());
}

TEST(RamFileBlockCacheTest, ValidateAndUpdateFileSignature) {
  int calls = 0;