code: def fake_faster_rcnn_model():
      class FakeRetinanetModel(nn.Module):
          def __init__(self):
              super().__init__()
              # hack for the function `model_device` to work
              self.layer = nn.Linear(1, 1)
  
          def forward(self, *args, **kwargs):
              return [
                  {
                      "scores": tensor([0.8, 0.9]),
                      "labels": tensor([1, 2]),
                      "boxes": tensor(
                          [[10, 10, 50, 50], [20, 20, 40, 40]]
                      ),
                  }
              ]
  
      return FakeRetinanetModel()
  
imports: import pytest
  from icevision.all import *
  from icevision.models.torchvision import retinanet
label_desc: Use image node_id 1 for calling a global function with example usage: fake_faster_rcnn_model() and returns: FakeRetinanetModel, list