key: "output_types"
    value {
      list {
        type: DT_BFLOAT16
        type: DT_FLOAT
        type: DT_DOUBLE
      }
    }
  }
}
node {
  name: "IteratorGetNextSync"
  op: "IteratorGetNextSync"
  input: "args_0"
  attr {
    key: "output_shapes"
    value {
      list {
        shape {
          unknown_rank: true
        }
        shape {
          dim {

  REGISTER_KERNEL_BUILDER(Name("IteratorGetNextAsOptional").Device(DEVICE),    \
                          data::IteratorGetNextAsOptionalOp);                  \
  REGISTER_KERNEL_BUILDER(Name("IteratorGetNextSync").Device(DEVICE),          \
                          data::IteratorGetNextOp);                            \
  REGISTER_KERNEL_BUILDER(Name("IteratorToStringHandle")                       \

    return ConvertToMlirTensorType(output_shape, element_type, &builder);
  };

  if (node.type_string() == "IteratorGetNext" ||
      node.type_string() == "IteratorGetNextSync" ||
      node.type_string() == "MultiDeviceIteratorGetNextFromShard")
    return type_from_array_attr("output_shapes", "output_types");

  if (node.type_string() == "InfeedDequeueTuple")

    ConfinedAttr<TF_ShapeAttrArray, [ArrayMinCount<1>]>:$output_shapes
  );

  let results = (outs
    TF_VariantTensor:$optional
  );
}

def TF_IteratorGetNextSyncOp : TF_Op<"IteratorGetNextSync", []> {
  let summary = "Gets the next output from the given iterator.";

  let description = [{
This operation is a synchronous version IteratorGetNext. It should only be used