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THOP: PyTorch-OpCounter

How to install

  • Through PyPi

    pip install thop

  • Using GitHub (always latest)

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

How to use

  • Basic usage

    from torchvision.models import resnet50
    from thop import profile
    model = resnet50()
    input = torch.randn(1, 3, 224, 224)
    flops, 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)
    flops, 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
    flops, params = clever_format([flops, params], "%.3f")
    

Results on Recent Models

Model Params(M) MACs(G)
alexnet 58.27 0.72
densenet121 7.61 2.70
densenet161 27.35 7.31
densenet169 13.49 3.20
densenet201 19.09 4.09
resnet18 11.15 1.70
resnet34 20.79 3.43
resnet50 24.37 3.85
resnet101 42.49 7.33
resnet152 57.40 10.81
Model Params(M) MACs(G)
squeezenet1_0 1.19 0.77
squeezenet1_1 1.18 0.33
vgg11 126.71 7.21
vgg11_bn 126.71 7.24
vgg13 126.88 10.66
vgg13_bn 126.89 10.70
vgg16 131.95 14.54
vgg16_bn 131.96 14.59
vgg19 137.01 18.41
vgg19_bn 137.02 18.47

Metadata

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0.0.30-1908281655 This release

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