text: # Copyright (c) Facebook, Inc. and its affiliates.
  
  
  import unittest
  import torch
  
  from detectron.utils.analysis import flop_count_operators, parameter_count
  from detectron.utils.testing import get_model_no_weights
  
  
  class RetinaNetTest(unittest.TestCase):
      def setUp(self):
          self.model = get_model_no_weights("COCO-Detection/retinanet_R_50_FPN_1x.yaml")
  
      def test_flop(self):
          # RetinaNet supports flop-counting with random inputs
          inputs = [{"image": torch.rand(3, 800, 800), "test_unused": "abcd"}]
          res = flop_count_operators(self.model, inputs)
          self.assertTrue(int(res["conv"]), 146)  # 146B flops
  
      def test_param_count(self):
          res = parameter_count(self.model)
          self.assertTrue(res[""], 37915572)
          self.assertTrue(res["backbone"], 31452352)
  
  
  class FasterRCNNTest(unittest.TestCase):
      def setUp(self):
          self.model = get_model_no_weights("COCO-Detection/faster_rcnn_R_50_FPN_1x.yaml")
  
      def test_flop(self):
          # Faster R-CNN supports flop-counting with random inputs
          inputs = [{"image": torch.rand(3, 800, 800)}]
          res = flop_count_operators(self.model, inputs)
  
          # This only checks flops for backbone & proposal generator
          # Flops for box head is not conv, and depends on #proposals, which is
          # almost 0 for random inputs.
          self.assertTrue(int(res["conv"]), 117)
  
      def test_param_count(self):
          res = parameter_count(self.model)
          self.assertTrue(res[""], 41699936)
          self.assertTrue(res["backbone"], 26799296)
  