EXPECT_EQ(TF_OUT_OF_RANGE, TF_GetCode(s_));
  EXPECT_EQ(string("Node 'feed2' (type: 'Placeholder', num of outputs: 1) does "
                   "not have output 2\n\tEncountered while processing "
                   "input 1 into function 'MyFunc'"),
            string(TF_Message(s_)));
}

TEST_F(CApiFunctionTest, InvalidInputTensor_BadNodePtr) {
  /*
   *                  |  |

*   Adds support for a new "distributed_epoch" processing mode. This processing
    mode distributes a dataset across all tf.data workers, instead of having
    each worker process the full dataset. See
    [the tf.data service docs](https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#understand_processing_mode)
    to learn more.

                    absl::Span<const tensorflow::DataType> dtypes);

  // Temporarily push or pop transient state for this accumulator.
  //
  // Allows an accumulator which is currently processing an operation to
  // temporarily reset its state. Without pushing and popping, accumulators
  // ignore operations executed as a direct result of their own jvp
  // computations.

    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,
                                    " into function '", fn_name, "'");

    input_tensors->emplace_back(node, idx);