code: def __call__(self, x: Tensor):
      for downsample, stage in zip(self.downsample_layers, self.stages):
          x = x.sequential(downsample).sequential(stage)
      return x.mean([-2, -1]).sequential([self.norm, self.head])
  
file_path: tinygrad/extra/models/convnext.py
imports: from tinygrad.tensor import Tensor
  from tinygrad.nn import Conv2d, LayerNorm, LayerNorm2d, Linear
  from tinygrad.helpers import fetch, get_child
label_desc: Use image node_id 2 for calling the ConvNeXt obj's underlying member method code with example usage: obj.__call__(x) and returns: x