// CHECK: [[body_res:%.*]]:2 = tfrt.call @while_body_add2([[ch]], [[arg]]) : (!tfrt.chain, !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
// CHECK: [[pred_res:%.*]]:2 = tfrt.call @"while_cond_lt9/tfrt_predicate"([[body_res]]#0, [[body_res]]#1) : (!tfrt.chain, !tfrt_fallback.tf_tensor) -> (!tfrt.chain, i1)

    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) {

  if (!s.ok()) {
    ::tensorflow::Set_TF_Status_from_Status(status, s);
    return nullptr;
  }
  TF_Tensor* tf_tensor = TF_TensorFromTensor(*tensor, &s);
  if (!s.ok()) {
    ::tensorflow::Set_TF_Status_from_Status(status, s);
    return nullptr;
  }
  return tf_tensor;
}

TF_Tensor* TF_ForwardInputOrAllocateOutput(
    TF_OpKernelContext* context, const int* candidate_input_indices,

#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"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/stringpiece.h"
#include "tensorflow/core/platform/test.h"

#include "tensorflow/c/kernels.h"
#include "tensorflow/c/kernels_experimental.h"
#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/c/tf_tensor_internal.h"
#include "tensorflow/compiler/jit/variable_info.h"
#include "tensorflow/compiler/jit/variable_info_util.h"
#include "xla/pjrt/c/pjrt_c_api.h"

    CPred<"$_self.isa<mlir::TFR::" # name # "Type>()">,
    "TFR " # name #" type">,
    BuildableType<"$_builder.getType<mlir::TFR::" # name # "Type>()">;
def TFR_TensorType : TFR_Type<"TFRTensor">;
def TFR_TensorListType : TFR_Type<"TFRTensorList">;
def TFR_AllTensorTypes : Type<Or<[
    TFR_TensorType.predicate,
    TFR_TensorListType.predicate]>, "all tensor related types">;

// attribute argument types

    TFE_Context* ctx) {
  return static_cast<TFE_ContextDevicePlacementPolicy>(
      tensorflow::unwrap(ctx)->GetDevicePlacementPolicy());
}

TFE_TensorHandle* TFE_NewTensorHandle(const TF_Tensor* t, TF_Status* status) {
  tensorflow::Tensor tensor;
  status->status = tensorflow::TF_TensorToTensor(t, &tensor);
  if (!status->status.ok()) return nullptr;