code: def _forward_impl(self, x: Tensor) -> Tensor:
      # This exists since TorchScript doesn't support inheritance, so the superclass method
      # (this one) needs to have a name other than `forward` that can be accessed in a subclass
      x = self.features(x)
      # Cannot use "squeeze" as batch-size can be 1
      x = nn.functional.adaptive_avg_pool2d(x, (1, 1))
      x = torch.flatten(x, 1)
      x = self.classifier(x)
      return x
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional
  import torch
  from torch import nn, Tensor
  from ..ops.misc import Conv2dNormActivation
  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 2 for calling the MobileNetV2 obj's underlying member method code with example usage: obj._forward_impl(x) and returns: x