func.func @returns_multiple_refs(%ch: !tfrt.chain, %a: !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor) {
  tfrt.return %ch, %a, %a : !tfrt.chain, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor
}

// ... when the function returns_multiple_refs is invoked by the batch_function,
// ... then the code should not crash.

#include <string>

#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/strcat.h"

namespace tensorflow {

std::string ShapeDebugString(TF_Tensor* tensor) {
  // A TF_Tensor cannot have an unknown rank.
  CHECK_GE(TF_NumDims(tensor), 0);
  tensorflow::string s = "[";
  for (int i = 0; i < TF_NumDims(tensor); ++i) {

              !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor,

#include <memory>

#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class Tensor;

Status TF_TensorToTensor(const TF_Tensor* src, Tensor* dst);

TF_Tensor* TF_TensorFromTensor(const Tensor& src, Status* status);

TF_Tensor* TF_TensorFromTensorShallow(const Tensor& src, Status* status);

namespace internal {

struct TFTensorDeleter {

//   2. The variable is initialized
//   3. The shape of the value tensor doesn't match the shape of the variable
//      tensor.
TF_CAPI_EXPORT extern void TF_AssignVariable(
    TF_OpKernelContext* ctx, int input_index, int value_index,
    bool validate_shape,
    void (*copyFunc)(TF_OpKernelContext* ctx, TF_Tensor* source,
                     TF_Tensor* dest),
    TF_Status* status);

  %out_ch, %result = tfrt.call @callee(%ch, %arg) : (!tfrt.chain, !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
  tfrt.return %out_ch, %result : !tfrt.chain, !tfrt_fallback.tf_tensor

// CHECK-SAME: [[arg0:%.*]]: !tfrt_fallback.tf_tensor,
// CHECK-SAME: [[arg1:%.*]]: !tfrt_fallback.tf_tensor)
// CHECK-SAME: -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
func.func @func_basic(
    %arg0: tensor<3x1xf32> {tf_saved_model.index_path = [0]},
    %arg1: tensor<!tf_type.resource<tensor<1x3xf32>>> {tf_saved_model.index_path = [1]})
      -> (tensor<3x3xf32> {tf_saved_model.index_path = []})

  for (TFE_TensorHandle* tensor_handle : outputs) {
    TF_Tensor* tf_tensor = TFE_TensorHandleResolve(tensor_handle, status);
    RETURN_FAILURE_IF_ERROR(status);
    auto clean_tensor =
        MakeCleanup([tf_tensor] { TF_DeleteTensor(tf_tensor); });
    Tensor tensor;
    RETURN_FAILURE_IF_ERROR(TF_TensorToTensor(tf_tensor, &tensor));
    auto attr_or = ConvertTensor(tensor, &builder);
    RETURN_FAILURE_IF_ERROR(attr_or.status());

}


def TF_IfrtLoadVariableOp : TF_Op<"IfrtLoadVariable", [Pure]> {
  let summary = "Loads a restored variable tensor as a tensor future";

  let description = [{
    This op loads a restored variable tensor as a tensor future. It is a
    replacement of `tf.ReadVariableOp`.

    This op returns a scalar string tensor containing the restored variable name, which 

}

// This corresponds to tensorflow::Tensor.
def TFTensorType : DialectType<Fallback_Dialect,
    CPred<"$_self.isa<::tfrt::fallback::TFTensorType>()">, "!tfrt_fallback.tf_tensor type">,
    BuildableType<"$_builder.getType<::tfrt::fallback::TFTensorType>()"> {
  let description = [{
    `!tfrt_fallback.tf_tensor type` represents a tensorflow::Tensor.
  }];
}

// This corresponds to tensorflow::Allocator.