// The input handles should never change since they have been mirrored.
    ASSERT_FALSE(remote_arg->HasLocalMirror(nullptr));
  }

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  // TODO(gjn): Add support for waiting on async local mirrors

		key.Extension = "." + vals[1]
		key.Name = strings.TrimSuffix(key.Name, key.Extension)
	}
	return
}

// replayItems - Reads the items from the store and replays.
func replayItems[I any](store Store[I], doneCh <-chan struct{}, log logger, id string) <-chan Key {
	keyCh := make(chan Key)

	go func() {
		defer xioutil.SafeClose(keyCh)

  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  float product[4] = {0};

                                 ForwardOperation*);

// Make the call to `Tape::RecordOperation`.
absl::Status Execute(AbstractOperation*, AbstractContext*,
                     absl::Span<AbstractTensorHandle*> retvals,
                     int* num_retvals, ForwardOperation*, Tape*,
                     const GradientRegistry&);

}  // namespace internal
}  // namespace gradients
}  // namespace tensorflow

  virtual absl::Status AddInput(AbstractTensorHandle* input) = 0;
  virtual absl::Status AddInputList(
      absl::Span<AbstractTensorHandle* const> inputs) = 0;
  virtual absl::Status Execute(absl::Span<AbstractTensorHandle*> retvals,
                               int* num_retvals) = 0;

  virtual absl::Status SetAttrString(const char* attr_name, const char* data,
                                     size_t length) = 0;