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

  TFE_TensorHandle* raw_result_handle;
  int num_retvals = 1;
  TFE_Execute(op.get(), &raw_result_handle, &num_retvals, status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  TensorHandlePtr reduced(raw_result_handle);

  std::array<TensorHandlePtr, 2> result_components;

    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    {
      AbstractContext* ctx_raw = nullptr;
      status_ =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
      ASSERT_EQ(errors::OK, status_.code()) << status_.message();
      immediate_execution_ctx_.reset(ctx_raw);
    }

    // Computing numerical gradients with TensorFloat-32 is numerically

  void Release() override { delete this; }
  Status Reset(const char* op, const char* raw_device_name) override {
    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();
  }

        output->Unref();
      }
      TF_RETURN_IF_ERROR(ctx->RegisterFunction(func));
    }

    AbstractOperationPtr fn_op(ctx->CreateOperation());
    TF_RETURN_IF_ERROR(fn_op->Reset(fn_name, /*raw_device_name=*/nullptr));
    for (auto input : inputs) {
      TF_RETURN_IF_ERROR(fn_op->AddInput(input));
    }
    int retvals = outputs.size() - null_indices.size();

  // parent_op->Unref();
}
Status TapeOperation::Reset(const char* op, const char* raw_device_name) {
  forward_op_.op_name = op;
  forward_op_.attrs.Reset(op);
  forward_op_.inputs.clear();
  forward_op_.outputs.clear();
  return parent_op_->Reset(op, raw_device_name);
}
const string& TapeOperation::Name() const { return parent_op_->Name(); }
const string& TapeOperation::DeviceName() const {

void TFE_OpReset(TFE_Op* op_to_reset, const char* op_or_function_name,
                 const char* raw_device_name, TF_Status* status) {
  if (op_to_reset) {
    tensorflow::ImmediateExecutionOperation* op =
        tensorflow::unwrap(op_to_reset);
    op->Clear();
    status->status = op->Reset(op_or_function_name, raw_device_name);
  } else {
    TF_SetStatus(status, TF_INVALID_ARGUMENT,

    EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_DeleteTensorHandle(n);
    n = n_gpu;
  }

  TFE_TensorHandle* m = TestMatrixTensorHandle100x100(ctx);

  // Store pointer to raw buffer for validation of forwarding behaviour.
  TF_Tensor* orig = TFE_TensorHandleResolve(n, status);
  void* orig_ptr = TF_TensorData(orig);
  TF_DeleteTensor(orig);

  TFE_Op* add_op = AddOp(ctx, n, m);