code: def simplify_split_cat(
      match: Match, split_sections: List[int], dim: int
  ):
      if not isinstance(
          split_sections, (list, tuple)
      ):  # Unnormalized split
          return
      split_node = next(
          node for node in match.nodes if node.target == torch.split
      )
      SplitCatSimplifier().simplify(
          match.graph, split_node, split_sections
      )
  
imports: import itertools
  import logging
  import operator
  from typing import Any, Callable, List, Optional, Sequence, Set, Tuple, Union
  from typing_extensions import TypeAlias
  import torch
  from torch._dynamo.utils import counters
  from ..pattern_matcher import Arg, CallFunction, CallFunctionVarArgs, CallMethodVarArgs, config_flag, FailedMatch, get_arg_value, Ignored, KeywordArg, ListOf, Match, MatchContext, MULTIPLE, PatternExpr, register_graph_pattern, RepeatedExpr
  from .pre_grad import merge_getitem_cat_pass, merge_splits_pass, normalization_pass, split_cat_pass, unbind_stack_pass
label_desc: Use image node_id 12 for calling a global function with example usage: simplify_split_cat(match, split_sections, dim) without return types