THOP

https://github.com/Lyken17/pytorch-OpCounter
pip install thop（推荐用这个） 或者 pip install —upgrade git+https://github.com/Lyken17/pytorch-OpCounter.git（这个方法需要同时安装pytorch）

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

ptflops

pip install ptflops 或者 pip install —upgrade git+https://github.com/sovrasov/flops-counter.pytorch.git
https://github.com/sovrasov/flops-counter.pytorch

import torchvision.models as models
import torch
from ptflops import get_model_complexity_info
with torch.cuda.device(0):
  net = models.densenet161()
  macs, params = get_model_complexity_info(net, (3, 224, 224), as_strings=True,
                                           print_per_layer_stat=True, verbose=True)
  print('{:<30}  {:<8}'.format('Computational complexity: ', macs))
  print('{:<30}  {:<8}'.format('Number of parameters: ', params))