// SECTION 3. Implementation for `TF_ReadOnlyMemoryRegion`
// ----------------------------------------------------------------------------
namespace tf_read_only_memory_region {

// TODO(b/139060984): Implement later

}  // namespace tf_read_only_memory_region

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------

    *value = it->second.value;
    lru_list_.push_front(it->first);
    it->second.lru_iterator = lru_list_.begin();
    return true;
  }

  void InsertLocked(const std::string& key, const T& value)
      ABSL_EXCLUSIVE_LOCKS_REQUIRED(mu_) {
    lru_list_.push_front(key);
    Entry entry{timer_seconds_(), value, lru_list_.begin()};
    auto insert = cache_.insert(std::make_pair(key, entry));
    if (!insert.second) {

// completed. The memory returned might alias the internal memory used by
// TensorFlow. Hence, callers should not mutate this memory (for example by
// modifying the memory region pointed to by TF_TensorData() on the returned
// TF_Tensor).
TF_CAPI_EXPORT extern TF_Tensor* TFE_TensorHandleResolve(TFE_TensorHandle* h,
                                                         TF_Status* status);

  } else {
    if (!desc->colocation_constraints.empty()) {
      desc->node_builder.Attr(
          tensorflow::kColocationAttrName,
          std::vector<string>(desc->colocation_constraints.begin(),
                              desc->colocation_constraints.end()));
    }
    status->status = desc->node_builder.Finalize(&desc->graph->graph, &ret,
                                                 /*consume=*/true);

  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();

  TapeVSpace vspace(ctx);
  std::vector<int64_t> target_tensor_ids = MakeTensorIDList(targets);
  std::vector<int64_t> source_tensor_ids = MakeTensorIDList(sources);
  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) {

    ],
    visibility = [
        "//tensorflow/c:__subpackages__",
        "//tensorflow/cc/experimental/libtf:__pkg__",
        "//tensorflow/cc/experimental/libtf:__subpackages__",
        # copybara:uncomment_begin(google-only)
        # "//tensorflow/cc/experimental/tf2:__pkg__",
        # "//tensorflow/cc/experimental/tf2:__subpackages__",
        # copybara:uncomment_end

  std::unique_ptr<ReadOnlyMemoryRegion> region;
  status = env_->NewReadOnlyMemoryRegionFromFile(filepath, &region);
  EXPECT_PRED2(UnimplementedOrReturnsCode, status, Code::OK);
  if (!status.ok())
    GTEST_SKIP() << "NewReadOnlyMemoryRegionFromFile() not supported: "
                 << status;
  EXPECT_EQ(region->length(), test_data.size());
  EXPECT_STREQ(reinterpret_cast<const char*>(region->data()),
               test_data.c_str());

    }
    auto begin = data.begin();
    if (offset > pos) {
      // The block begins before the slice we're reading.
      begin += offset - pos;
    }
    auto end = data.end();
    if (pos + data.size() > offset + n) {
      // The block extends past the end of the slice we're reading.
      end -= (pos + data.size()) - (offset + n);
    }
    if (begin < end) {

  ops_->new_read_only_memory_region_from_file(
      filesystem_.get(), translated_name.c_str(), region.get(),
      plugin_status.get());

  if (TF_GetCode(plugin_status.get()) == TF_OK)
    *result = std::make_unique<ModularReadOnlyMemoryRegion>(
        std::move(region), read_only_memory_region_ops_.get());

  return StatusFromTF_Status(plugin_status.get());
}