void (*binary_add_func)(TF_OpKernelContext* ctx, TF_Tensor* a, TF_Tensor* b,
                            TF_Tensor* out));

static Status CCBinaryAddFunc(
    ::tensorflow::OpKernelContext* cc_ctx, const Tensor& cc_a,
    const Tensor& cc_b, Tensor* cc_out,
    void (*binary_add_func)(TF_OpKernelContext* ctx, TF_Tensor* a, TF_Tensor* b,
                            TF_Tensor* out)) {
  if (cc_a.dtype() == ::tensorflow::DT_INVALID) {

  tfrt.return %ch1 : !tfrt.chain
}

// Test to verify the fix for b/190394141:
// Given a function that returns multiple values referenced to the same value,
func.func @returns_multiple_refs(%ch: !tfrt.chain, %a: !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor) {

  }];

  let arguments = (ins
    TF_Tensor:$cond,
    Variadic<TF_Tensor>:$input,

    FlatSymbolRefAttr:$then_branch,
    FlatSymbolRefAttr:$else_branch,

    // Used to map StatelessIf and If op defined in TensorFlow to a common op.
    BoolAttr:$is_stateless
  );

  let results = (outs
    Variadic<TF_Tensor>:$output
  );

namespace {

// Operators used to create a std::unique_ptr for TF_Tensor and TF_Status
struct TFTensorDeleter {
  void operator()(TF_Tensor* tf_tensor) const { TF_DeleteTensor(tf_tensor); }
};

struct TFStatusDeleter {
  void operator()(TF_Status* tf_status) const { TF_DeleteStatus(tf_status); }
};

// Struct that wraps TF_Tensor and TF_Status to delete once out of scope

#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/platform/types.h"

namespace {

// Struct that stores the status and TF_Tensor inputs to the opkernel.
// Used to delete tensor and status in its destructor upon kernel return.
struct Params {
  TF_Tensor* tags;
  TF_Tensor* values;
  TF_Status* status;
  explicit Params(TF_OpKernelContext* ctx)
      : tags(nullptr), values(nullptr), status(nullptr) {

    Tensor tensor;
    RETURN_FAILURE_IF_ERROR(ConvertToTensor(operand, &tensor));
    TF_Tensor* tf_tensor = TF_TensorFromTensor(tensor, &status->status);
    RETURN_FAILURE_IF_ERROR(status);
    auto clean_tensor =
        MakeCleanup([tf_tensor] { TF_DeleteTensor(tf_tensor); });
    TFE_TensorHandle* input_handle = TFE_NewTensorHandle(tf_tensor, status);
    RETURN_FAILURE_IF_ERROR(status);
    auto clean_input_handle =

// CHECK-NEXT: tfrt.return [[out_chain]], [[o9]], [[o5]], [[o8]], [[o6]], [[arg1]], [[o3]] : !tfrt.chain, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor, !tfrt_fallback.tf_tensor

// Validates that the tensor has shape and type corresponding to
// dims and dtype.
void validate_tensor(TF_Tensor* tensor, int64_t* dims, int64_t num_dims,
                     TF_DataType dtype);

// Copies data of length tensor_size_bytes from values to tensor.
template <typename T>
void set_tensor_data(TF_Tensor* tensor, T* values, size_t tensor_size_bytes,
                     TF_OpKernelContext* ctx);

#include <string>

#include "tensorflow/c/tf_tensor.h"

namespace tensorflow {

// The following are utils for the shape of a TF_Tensor type.
// These functions may later be subsumed by the methods for a
// TF_TensorShape type.

// Returns a string representation of the TF_Tensor shape.
std::string ShapeDebugString(TF_Tensor* tensor);

}  // namespace tensorflow

    Other ops executed by TFRT may make use of $tensor_future.
  }];

  let arguments = (ins
    Arg<TF_Tensor, [{The variable tensor to be loaded}], []>:$variable,
    DefaultValuedAttr<BoolAttr, "false">:$used_by_host
  );

  let results = (outs
    TF_StrTensor:$array_key,
    TF_Tensor: $tensor_future
  );

  TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<0>;