docstr: Return an iterator over AnyNet parameters for each stage.
docstr_tok: ["Return","an","iterator","over","AnyNet","parameters","for","each","stage","."]
code: def get_expanded_params(self):
      """Return an iterator over AnyNet parameters for each stage."""
      return zip(
          self.widths,
          self.strides,
          self.depths,
          self.group_widths,
          self.bottleneck_multipliers,
      )
  
imports: import math
  from collections import OrderedDict
  from enum import auto, Enum
  from typing import Any, Dict, Optional, Sequence
  import torch.nn
  from classy_vision.generic.util import get_torch_version
  from classy_vision.models import ClassyModel, register_model
  from classy_vision.models.squeeze_and_excitation_layer import SqueezeAndExcitationLayer
label_desc: Use image node_id 2 for calling the AnyNetParams obj's underlying member method code with example usage: obj.get_expanded_params() and returns: zip