code: def __init__(
      self,
      input_channels: int,
      kernel: int,
      expanded_channels: int,
      out_channels: int,
      use_se: bool,
      activation: str,
      stride: int,
      dilation: int,
      width_mult: float,
  ):
      self.input_channels = self.adjust_channels(
          input_channels, width_mult
      )
      self.kernel = kernel
      self.expanded_channels = self.adjust_channels(
          expanded_channels, width_mult
      )
      self.out_channels = self.adjust_channels(out_channels, width_mult)
      self.use_se = use_se
      self.use_hs = activation == "HS"
      self.stride = stride
      self.dilation = dilation
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Sequence
  import torch
  from torch import nn, Tensor
  from ..ops.misc import Conv2dNormActivation, SqueezeExcitation
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _make_divisible, _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 1 to create a new InvertedResidualConfig object  with example: obj = InvertedResidualConfig(input_channels, kernel, expanded_channels, out_channels, use_se, activation, stride, dilation, width_mult)