code: def __init__(self, cfg: SegmentationConfig):
      super().__init__()
      self.cfg = cfg
      self.subsample_rate = cfg.subsample_rate
  
imports: from dataclasses import dataclass
  from enum import Enum, auto
  import math
  import numpy
  from typing import Tuple, List, Optional, Dict
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import autograd
  from fairseq import checkpoint_utils, utils
  from fairseq.dataclass import FairseqDataclass
  from fairseq.models import BaseFairseqModel, register_model
  from fairseq.modules import SamePad, TransposeLast
label_desc: Use image node_id 1 to create a new Segmenter object from inherited base classes: nn with example: obj = Segmenter(cfg)