for (int i = 0; i < num_inputs; ++i) {
    TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, i, status);
    if (TF_GetCode(status) != TF_OK) return;
    const char* tensor_handle_device =
        TFE_TensorHandleDeviceName(input, status);
    if (TF_GetCode(status) != TF_OK) return;
    if (named_device->name() == tensor_handle_device) {
      // We assume that any tensors already placed on this device are

    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

    TF_RETURN_WITH_CONTEXT_IF_ERROR(
        fn_body->graph.IsValidOutputTensor(node, idx),
        "Encountered while processing input ", i, " into function '", fn_name,
        "'");
    TF_RETURN_WITH_CONTEXT_IF_ERROR(ValidateNonRefOutput(node, idx),
                                    "Encountered while processing input ", i,

                                       status_);
    if (TF_GetCode(status_) != TF_OK) return;
    tf_writable_file::Append(writer.get(), content.c_str(), content.length(),
                             status_);
    if (TF_GetCode(status_) != TF_OK) return;
    tf_writable_file::Close(writer.get(), status_);
    if (TF_GetCode(status_) != TF_OK) return;
  }

        TFE_DeleteOp);
    if (TF_GetCode(status.get()) != TF_OK) return;
    TFE_OpSetAttrInt(op.get(), "num_replicas", 1);
    TFE_OpAddInput(op.get(), value_one.get(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) return;
    TFE_OpSetDevice(op.get(), device_name, status.get());
    if (TF_GetCode(status.get()) != TF_OK) return;

    TFE_TensorHandle* result_handles;

 public:
  static bool enabled_;
  GraphErrorInjectionPass() {}

  tensorflow::Status Run(
      const tensorflow::GraphOptimizationPassOptions& options) override {
    if (!enabled_) {
      return absl::OkStatus();
    }
    if (first_call_) {
      first_call_ = false;
      return absl::OkStatus();
    }
    return tensorflow::errors::Internal("Graph pass runs for more than once!");
  }

 private:

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_EQ(0, device_id) << device_id;

  // Disable the test if no GPU is present.
  string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {
    TFE_TensorHandle* hgpu = TFE_TensorHandleCopyToDevice(
        hcpu, ctx, gpu_device_name.c_str(), status.get());

                                TF_RANDOM_ACCESS_FILE_OPS_ABI,
                                "random access file"));

  if (ops->writable_file_ops != nullptr)
    TF_RETURN_IF_ERROR(CheckABI(ops->writable_file_ops_abi,
                                TF_WRITABLE_FILE_OPS_ABI, "writable file"));

  if (ops->read_only_memory_region_ops != nullptr)

  *object = fname.substr(bucket_end + 1);

  if (object->empty() && !object_empty_ok) {
    TF_SetStatus(status, TF_INVALID_ARGUMENT,
                 "GCS path doesn't contain an object name.");
  }
}

/// Appends a trailing slash if the name doesn't already have one.
static void MaybeAppendSlash(std::string* name) {
  if (name->empty())
    *name = "/";
  else if (name->back() != '/')
    name->push_back('/');
}

    // Get transpose attrs
    bool t_a;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("transpose_a", &t_a));

    bool t_b;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("transpose_b", &t_b));

    // Conj each input
    AbstractTensorHandle* conj_output;
    std::string name = "Conj_A_MatMul_Grad";
    TF_RETURN_IF_ERROR(
        SafeConj(ctx, forward_inputs_[0], &conj_output, name.c_str()));

  if (!status->status.ok()) return nullptr;

  return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(tensor));
}

void TFE_DeleteTensorHandle(TFE_TensorHandle* h) {
  if (h == nullptr) return;

  tensorflow::profiler::TraceMe activity(
      "TFE_DeleteTensorHandle", tensorflow::profiler::TraceMeLevel::kInfo);
  if (h) {
    tensorflow::unwrap(h)->Unref();
  }