code: def forward(self, x):
      x = self._bn0(
          x.conv2d(self._conv_stem, padding=(0, 1, 0, 1), stride=2)
      ).swish()
      x = x.sequential(self._blocks)
      x = self._bn1(x.conv2d(self._conv_head)).swish()
      x = x.avg_pool2d(kernel_size=x.shape[2:4])
      x = x.reshape(shape=(-1, x.shape[1]))
      return (
          x.linear(self._fc, self._fc_bias)
          if self._fc is not None
          else x
      )
  
file_path: tinygrad/extra/models/efficientnet.py
imports: import math
  from tinygrad.tensor import Tensor
  from tinygrad.nn import BatchNorm2d
  from tinygrad.helpers import get_child, fetch
  from tinygrad.nn.state import torch_load
label_desc: Use image node_id 2 for calling the EfficientNet obj's underlying member method code with example usage: obj.forward(x) and returns: unknown