code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      x = self.squeeze_activation(self.squeeze(x))
      return torch.cat(
          [
              self.expand1x1_activation(self.expand1x1(x)),
              self.expand3x3_activation(self.expand3x3(x)),
          ],
          1,
      )
  
imports: from functools import partial
  from typing import Any, Optional
  import torch
  import torch.nn
  import torch.nn.init
  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 _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 2 for calling the Fire obj's underlying member method code with example usage: obj.forward(x) and returns: torch