// Attempts to look up the tensor named "name" and stores the found result in
  // "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.

  std::vector<TF_Output> return_tensors;
  std::vector<TF_Operation*> return_nodes;
  std::vector<const char*> missing_unused_key_names;
  std::vector<int> missing_unused_key_indexes;

  // Backing memory for missing_unused_key_names values.
  std::vector<tensorflow::string> missing_unused_key_names_data;
};

struct TF_DeviceList {
  std::vector<tensorflow::DeviceAttributes> response;
};

struct TF_Function {

  return StatusFromTF_Status(plugin_status.get());
}

std::string ModularFileSystem::TranslateName(const std::string& name) const {
  if (ops_->translate_name == nullptr) return FileSystem::TranslateName(name);

  char* p = ops_->translate_name(filesystem_.get(), name.c_str());
  CHECK(p != nullptr) << "TranslateName(" << name << ") returned nullptr";

  std::string ret(p);
  // Since `p` is allocated by plugin, free it using plugin's method.

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),

  TF_OperationDescription* init(string type) {
    // Construct op_name to match the name used by REGISTER_OP in the
    // ATTR_TEST_REGISTER calls above.
    string op_name = "CApiAttributesTestOp";
    if (type.find("list(") == 0) {
      op_name += "List";
      type = type.replace(0, 5, "");
      type = type.replace(type.size() - 1, 1, "");
    }
    op_name += type;
    return TF_NewOperation(

  std::vector<string> input_names(ninputs);
  std::vector<string> output_names(noutputs);
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ninputs; ++i) {
    input_names[i] = c_input_names[i];
  }
  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }

  }
  std::sort(names.begin(), names.end());
  return names;
}

CSession::CSession(TF_Graph* graph, TF_Status* s, bool use_XLA) {
  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_EnableXLACompilation(opts, use_XLA);
  session_ = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);
}

CSession::CSession(TF_Session* session) : session_(session) {}

std::vector<IOSpec> M(const std::initializer_list<string>& names) {
  std::vector<IOSpec> v;
  for (const string& name : names) {
    v.push_back(IOSpec(name, DT_INVALID));
  }
  return v;
}

// Specification for an expected edge.
// src is either:
// - input name (as it appears in FunctionDef)
// - name of output tensor (in nested "add:z:0" format)
// dst is either:
// - output name (as it appears in FunctionDef)

  const std::vector<std::string>& op_names =
      tensorflow::unwrap(ctx)->GetLoggedOpsTestonly();

  std::ostringstream op_names_oss;
  for (const auto& op : op_names) {
    op_names_oss << op << ", ";
  }
  const std::string& op_names_str = op_names_oss.str();
  void* data = tensorflow::port::Malloc(op_names_str.length());
  op_names_str.copy(static_cast<char*>(data), op_names_str.length(), 0);
  buf->data = data;