limitations under the License.
==============================================================================*/
// This file extends/implements core graph optimizer base classes in terms of
// the C API defined in grappler.h. A class "CSomething" represents a
// "Something" that can be manipulated via calls in the C interface and a C
// struct called "TP_Something".

#include "tensorflow/c/experimental/grappler/grappler.h"

#include <algorithm>

  auto gcs_file = static_cast<GCSFile*>(file->plugin_file);
  if (!gcs_file->outfile.is_open()) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION,
                 "The internal temporary file is not writable.");
    return;
  }
  TF_VLog(3, "Append: gs://%s/%s size %u", gcs_file->bucket.c_str(),
          gcs_file->object.c_str(), n);
  gcs_file->sync_need = true;
  gcs_file->outfile.write(buffer, n);
  if (!gcs_file->outfile)

  if (ops->random_access_file_ops != nullptr)
    CheckAPI(ops->random_access_file_ops_api, TF_RANDOM_ACCESS_FILE_OPS_API,
             "random access file");

  if (ops->writable_file_ops != nullptr)
    CheckAPI(ops->writable_file_ops_api, TF_WRITABLE_FILE_OPS_API,
             "writable file");

  if (ops->read_only_memory_region_ops != nullptr)

    for (const EdgeSpec& e : e_edges) {
      ASSERT_TRUE(a_edges.find(e) != a_edges.end())
          << "Failed to find expected edge " << e.ToString()
          << " in fdef: " << fdef.DebugString();
    }
    for (const EdgeSpec& e : c_edges) {
      ASSERT_TRUE(a_edges.find(e) != a_edges.end())
          << "Failed to find expected control edge " << e.ToString()
          << " in fdef: " << fdef.DebugString();
    }

/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,

    if (op_) {
      return errors::FailedPrecondition("Reset called on already built op.");
    }
    if (raw_device_name) {
      device_name_ = raw_device_name;
    }
    op_type_ = op;
    return absl::OkStatus();
  }
  Status SetOpName(const char* const op_name) override {
    if (op_) {
      return errors::FailedPrecondition(
          "SetOpName called on already built op.");
    }
    if (op_type_.empty()) {

  tensorflow::unwrap(ctx)->SetThreadLocalDevicePlacementPolicy(
      static_cast<tensorflow::ContextDevicePlacementPolicy>(policy));
}

// Note: this function looks up a thread local policy. So it should be called in
// the appropriate client thread. In particular, in async mode, it may not be
// safe to call this function from the async EagerExecutor threads.
extern TFE_ContextDevicePlacementPolicy TFE_ContextGetDevicePlacementPolicy(