memset(&option, 0, sizeof(option));
  option.name = const_cast<char*>(name.c_str());
  TF_Filesystem_Option_Value option_value;
  memset(&option_value, 0, sizeof(option_value));
  option_value.type_tag = TF_Filesystem_Option_Type_Buffer;
  option_value.num_values = values.size();
  std::vector<TF_Filesystem_Option_Value_Union> option_values(values.size());
  for (size_t i = 0; i < values.size(); i++) {

    // Read the value of tensor handle `handle_1`.
    float value = 0.0f;
    TF_Tensor* t = TFE_TensorHandleResolve(handle_1, status);
    ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    ASSERT_EQ(sizeof(float), TF_TensorByteSize(t));
    memcpy(&value, TF_TensorData(t), sizeof(float));
    TF_DeleteTensor(t);
    EXPECT_EQ(1.2f, value);
    TFE_DeleteTensorHandle(handle_1);

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_Tensor* result_tensor = TFE_TensorHandleResolve(result_t, status.get());
  float* result_value = static_cast<float*>(TF_TensorData(result_tensor));
  EXPECT_EQ(*result_value, 4.0);

  TF_DeleteTensor(result_tensor);
  TF_DeleteAbstractTensor(result);
  TF_DeleteOutputList(o);
  TF_DeleteExecutionContext(ctx);
}

// MatMul Test

  executed = false;
  num_retvals = 1;
  TFE_TensorHandle* var_value = nullptr;
  TFE_Execute(op.get(), &var_value, &num_retvals, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_TRUE(executed);
  auto value_cleaner = tensorflow::gtl::MakeCleanup(
      [var_value]() { TFE_DeleteTensorHandle(var_value); });
  ASSERT_EQ(tensorflow::string(name),
            tensorflow::string(

                                                    const char* value,
                                                    TF_Status* status);

// Get configuration key and value using coordination service.
// The config key must be set before getting its value. Getting value of
// non-existing config keys will result in errors.
// If `timeout_in_ms=0`, this call will block until the key-value is set or the
// worker shuts down.

                   ForwardOperation* forward_op_) {
  forward_op_->attrs.Set(attr_name, value);
  return op_->SetAttrBool(attr_name, value);
}
Status SetAttrType(AbstractOperation* op_, const char* attr_name,
                   DataType value, ForwardOperation* forward_op_) {
  forward_op_->attrs.Set(attr_name, value);
  return op_->SetAttrType(attr_name, value);
}

    return false;
  }
  bool found_dtype = false;
  bool found_value = false;
  for (const auto& attr : node_def.attr()) {
    if (attr.first == "dtype") {
      if (attr.second.type() == tensorflow::DT_INT32) {
        found_dtype = true;
      } else {
        return false;
      }
    } else if (attr.first == "value") {
      if (attr.second.has_tensor() &&

                                               const void* value,
                                               size_t length);
TF_CAPI_EXPORT extern void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name,
                                            int64_t value);
TF_CAPI_EXPORT extern void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name,
                                              float value);

  auto s = tensorflow::unwrap(op)->SetAttrFloat(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrBool(TFE_Op* op, const char* attr_name, unsigned char value) {
  auto s = tensorflow::unwrap(op)->SetAttrBool(attr_name,
                                               (value == 0) ? false : true);
  if (!s.ok()) {

  } else {
    // Block until the key-value is set or the worker shuts down.
    timeout = absl::InfiniteDuration();
  }
  auto status_or_value = coord_agent->GetKeyValue(key, timeout);
  status->status = status_or_value.status();
  if (!status_or_value.ok()) return;

  const std::string& value_string = status_or_value.value();
  void* data = tensorflow::port::Malloc(value_string.length());