// order, and type) the op declaration.  For example, the "Concat" op
// has registration:
//   REGISTER_OP("Concat")
//       .Input("concat_dim: int32")
//       .Input("values: N * T")
//       .Output("output: T")
//       .Attr("N: int >= 2")
//       .Attr("T: type");
// that defines two inputs, "concat_dim" and "values" (in that order).

              "Internal state of the gradient tape is invalid: "
              "none of operations outputs match expected tensor");
        }
      } else {
        // This target tensor was not generated by any operation recorded on
        // the tape, so no gradient needs to be computed from it unless this
        // target is also a source.
        auto source_tensor = sources_that_are_targets.find(id);

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >
  BuildV2VarMaps();

  // Invariant: exactly one of "reader_" and "v2_reader_" is non-null.