In Keras, there is a detailed comparison of number of parameters and size in MB that model takes at Keras application page. Is there any similar resource in pytorch, where I can get a comparison of all model pretrained on imagenet and build using PyTorch. thanks
There is no place for all that information but you can get them one by one. For accuracy/error please visit torchvision.models.
For model stucture/params/size you can use
torchsummary in the same way in Keras.
import torchvision.models as models alexnet = models.alexnet(pretrained=True) alexnet.cuda() summary(alexnet, (3, 224, 224)) print(alexnet) # strcture - optional
It says model size but if you want to know the size of actual pretrained model, use
models.<model_name>(pretrained=True) and it will download the weights.