TF_SetStatus(status, TF_OK, "");
  if (retvals[0] != nullptr) {
    TFE_DeleteTensorHandle(retvals[0]);
  }
  retvals[0] = nullptr;
  TFE_Execute(matmul2, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status));
  TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
  EXPECT_EQ(TF_OK, TF_GetCode(status));
  TF_DeleteTensor(t);

    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
    TFE_TensorHandle* retvals[1];
    int num_retvals = 1;
    TFE_Execute(shape_op, &retvals[0], &num_retvals, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

    device_type = TFE_TensorHandleDeviceType(retvals[0], status.get());
    ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  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);

  auto* retval_task0 =
      TFE_TensorHandleCopyToDevice(retvals[0], ctx, local_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

                     int* num_retvals, ForwardOperation* forward_op_,
                     Tape* tape, const GradientRegistry& registry) {
  TF_RETURN_IF_ERROR(op_->Execute(retvals, num_retvals));
  for (int i = 0; i < *num_retvals; i++) {
    // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs.
    forward_op_->outputs.push_back(retvals[i]);
  }

                       ImmediateExecutionTensorHandle** retvals,
                       int* num_retvals) override {
    std::vector<TFE_TensorHandle*> outputs(*num_retvals);
    TF_Status status;
    device_.execute(tensorflow::wrap(op), num_retvals, outputs.data(), &status,
                    info_);
    if (status.status.ok()) {
      for (int i = 0; i < *num_retvals; ++i) {
        retvals[i] = tensorflow::unwrap(outputs[i]);

      }
      tf_outputs[i] = t->output_;
    }
    TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
    return absl::OkStatus();
  }
  absl::Status Execute(absl::Span<AbstractTensorHandle*> retvals,
                       int* num_retvals) override {
    auto* tf_opdesc = op_.release();
    if (tf_opdesc == nullptr) {
      return errors::InvalidArgument("AbstractOp is incomplete.");
    }

        int access = 123;

        // Mock the behavior of sendrecv for MsrpcLsarOpenPolicy2
        doAnswer(invocation -> {
            MsrpcLsarOpenPolicy2 rpc = invocation.getArgument(0);
            rpc.retval = 0; // Simulate success
            return null;
        }).when(mockDcerpcHandle).sendrecv(any(MsrpcLsarOpenPolicy2.class));

        // Act

        // Arrange
        int access = 0x01; // Example access value
        // Simulate successful RPC call
        doAnswer(invocation -> {
            MsrpcSamrOpenDomain rpc = invocation.getArgument(0);
            rpc.retval = 0; // Success
            return null;
        }).when(mockDcerpcHandle).sendrecv(any(MsrpcSamrOpenDomain.class));

        // Act

        int rid = 100;

        // Mock the behavior of sendrecv for MsrpcSamrOpenAlias
        doAnswer(invocation -> {
            MsrpcSamrOpenAlias rpc = invocation.getArgument(0);
            rpc.retval = 0; // Simulate success
            return null;
        }).when(mockDcerpcHandle).sendrecv(any(MsrpcSamrOpenAlias.class));

        // Act

            server = "\\\\";
        }
        final MsrpcLsarOpenPolicy2 rpc = new MsrpcLsarOpenPolicy2(server, access, this);
        handle.sendrecv(rpc);
        if (rpc.retval != 0) {
            throw new SmbException(rpc.retval, false);
        }
    }

    /**
     * Closes the LSA policy handle.
     *
     * @throws IOException if an I/O error occurs
     */
    public void close() throws IOException {