code: def __init__(
      self, resnet, out_channels=256, returned_layers=[2, 3, 4]
  ):
      self.out_channels = out_channels
      self.body = resnet
      in_channels_list = [
          (self.body.in_planes // 8) * 2 ** (i - 1)
          for i in returned_layers
      ]
      self.fpn = FPN(in_channels_list, out_channels)
  
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 1 to create a new ResNetFPN object  with example: obj = ResNetFPN(resnet, out_channels, returned_layers)