input_signature=[
              tensor_spec.TensorSpec(
                  name='x', shape=x_signature, dtype=dtypes.float32
              )
          ]
      )
      def einsum_with_kernel(self, x: core.Tensor) -> Mapping[str, core.Tensor]:
        return self._einsum(x, self._kernel)

      @def_function.function(
          input_signature=[
              tensor_spec.TensorSpec(

  const TaggedValueTensor& tensor() const { return get<TaggedValueTensor>(); }

  /// Retrieves underlying value from a TaggedValue with type TENSOR_SPEC.
  const TensorSpec& tensor_spec() const { return get<TensorSpec>(); }

  /// Retrieves underlying value from a TaggedValue with type CAPSULE.
  void* capsule() const { return get<impl::Capsule>().get(); }

  /// Retrieves type of TaggedValue.

    const mlir::Type& type) {
  DataType dtype;
  TF_RETURN_IF_ERROR(ConvertToDataType(type, &dtype));
  TensorSpecProto tensor_spec;
  tensor_spec.set_dtype(dtype);
  *tensor_spec.mutable_shape() = ConvertTypeToTensorShape(type).AsProto();
  return tensor_spec;
}

// Converts the tensor shape proto into an MLIR shape attribute.
absl::StatusOr<mlir::Attribute> ConvertTensorShapeProto(

#include "tensorflow/c/experimental/saved_model/public/signature_def_param.h"
#include "tensorflow/c/experimental/saved_model/public/signature_def_param_list.h"
#include "tensorflow/c/experimental/saved_model/public/tensor_spec.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_shape.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/lib/io/path.h"