code: def __call__(self, x):
      out = self.body.bn1(self.body.conv1(x)).relu()
      out = out.pad2d([1, 1, 1, 1]).max_pool2d((3, 3), 2)
      out = out.sequential(self.body.layer1)
      p3 = out.sequential(self.body.layer2)
      p4 = p3.sequential(self.body.layer3)
      p5 = p4.sequential(self.body.layer4)
      return self.fpn([p3, p4, p5])
  
imports: import math
  from tinygrad.helpers import flatten, get_child
  import tinygrad.nn
  from extra.models.resnet import ResNet
  import numpy
label_desc: Use image node_id 3 for calling the ResNetFPN obj's underlying member method code with example usage: obj.__call__(x) and returns: self