pip install thop (now continously intergrated on Github actions)

OR

pip install --upgrade git+https://github.com/Lyken17/pytorch-OpCounter.git

• Basic usage

  from torchvision.models import resnet50
  from thop import profile
  model = resnet50()
  input = torch.randn(1, 3, 224, 224)
  macs, params = profile(model, inputs=(input, ))

• Define the rule for 3rd party module.

  class YourModule(nn.Module):
      # your definition
  def count_your_model(model, x, y):
      # your rule here
  
  input = torch.randn(1, 3, 224, 224)
  macs, params = profile(model, inputs=(input, ), 
                          custom_ops={YourModule: count_your_model})

• Improve the output readability

  Call thop.clever_format to give a better format of the output.

  from thop import clever_format
  macs, params = clever_format([macs, params], "%.3f")

The implementation are adapted from torchvision. Following results can be obtained using benchmark/evaluate_famous_models.py.