// CHECK: Tensor<type: int32 shape: [2,2] values: [4 4]
  %ch1 = "tfrt_fallback_async.print_tensor"(%result_1, %ch0) : (!tfrt_fallback.tf_tensor, !tfrt.chain) -> !tfrt.chain

  // CHECK: Tensor<type: int32 shape: [2,2] values: [6 6]
  %ch2 = "tfrt_fallback_async.print_tensor"(%result_2, %ch1) : (!tfrt_fallback.tf_tensor, !tfrt.chain) -> !tfrt.chain

  tfrt.return %ch2 : !tfrt.chain
}

  string ret;
  for (int64_t i = 0; i < num_elts; ++i) {
    if (i > 0) strings::StrAppend(&ret, ", ");
    strings::StrAppend(&ret, array[i]);
  }
  return ret;
}

string PrintTensor(const TensorProto& tensor_proto);

string PrintTensorProto(const TensorProto& proto);

string PrintAttrValue(StringPiece, const AttrValue& attr_value);

bool IsEmptyList(const AttrValue::ListValue& list);

  for (int d = 0; d < shape.dims(); ++d) {
    if (d > 0) strings::StrAppend(&ret, ", ");
    strings::StrAppend(&ret, shape.dim_size(d));
  }
  strings::StrAppend(&ret, "}");
  return ret;
}

string PrintTensor(const TensorProto& tensor_proto) {
  Tensor t(tensor_proto.dtype());
  CHECK(t.FromProto(tensor_proto));
  const int64_t num_elts = t.NumElements();
  switch (t.dtype()) {
    case DT_FLOAT:

*   Changed references to LIBXSMM to use version 1.8.1.
*   TensorFlow Debugger (tfdbg):
    *   Display summaries of numeric tensor values with the `-s` flag to command
        `print_tensor` or `pt`.
    *   Display feed values with the `print_feed` or `pf` command and clickable
        links in the curses UI.
    *   Runtime profiler at the op level and the Python source line level with