code: def use_segment_matmul_heuristic(
      num_segments: int,
      max_segment_size: int,
      in_channels: int,
      out_channels: int,
  ) -> bool:
      r"""A heuristic based on input sizes to determine whether the usage of
      :meth:`segment_matmul` can speed up computation.
      """
      # NOTE This heuristic was learned on an A100 via sklearn using a simple
      # StandardScaler() -> LinearSVC() model.
      x = torch.tensor(
          [
              num_segments,
              max_segment_size,
              in_channels,
              out_channels,
          ]
      )
      mean = torch.tensor(
          [
              125.11603189,
              12133.21523472,
              163.81222321,
              32.43755536,
          ]
      )
      std = torch.tensor(
          [
              163.34480422,
              27572.94543809,
              177.6426489,
              56.82103934,
          ]
      )
      weight = torch.tensor(
          [
              2.43877659e00,
              1.67583047e00,
              -5.20527282e-04,
              3.43925501e-01,
          ]
      )
      bias = 1.20236999
  
      x = (x - mean) / std
      return bool(x @ weight >= bias)
  
label_desc: Use image node_id 1 for calling a global function with example usage: use_segment_matmul_heuristic(num_segments, max_segment_size, in_channels, out_channels) and returns: bool