code: def spec_retinanet():
      # Retinanet with ResNet backbone
      from extra.models.resnet import ResNet50
      from extra.models.retinanet import RetinaNet
  
      mdl = RetinaNet(ResNet50(), num_classes=91, num_anchors=9)
      img = Tensor.randn(1, 3, 224, 224)
      test_model(mdl, img)
  
file_path: tinygrad/examples/mlperf/model_spec.py
imports: from tinygrad import Tensor, GlobalCounters
  from tinygrad.helpers import getenv
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: spec_retinanet() without return types