code: def _register_quantized_cat_lowering(
      pattern,
      computation_op,
  ):
      @register_lowering_pattern(
          pattern,
          extra_check=_is_input_output_same_scale_zp(aten.cat.default),
      )
      def qcat(match: Match, inputs, dim, **kwargs):
          # inputs is with format: [[x1, x1_dq_dtype, x1_zp, x1_scale], ...]
          uint8_inputs = [input[0] for input in inputs]
          return L[computation_op](uint8_inputs, dim)
  
      return qcat
  
imports: import copy
  import functools
  import itertools
  import math
  import operator
  from typing import Any, Tuple
  import torch
  from torch._dynamo.utils import counters
  from torch.fx.experimental.symbolic_shapes import has_free_symbols
  from ..lowering import lowerings, require_channels_last
  from ..pattern_matcher import Arg, CallFunction, filter_nodes, KeywordArg, ListOf, Match
  from ..utils import pad_listlike
  from .freezing_patterns import register_freezing_graph_pattern
  from .post_grad import register_lowering_pattern
label_desc: Use image node_id 20 for calling a global function with example usage: _register_quantized_cat_lowering(pattern, computation_op) and returns: qcat, L