torchvision.models

torchvision.models模块的 子模块中包含以下模型结构。

• AlexNet
• VGG
• ResNet
• SqueezeNet
• DenseNet You can construct a model with random weights by calling its constructor:

你可以使用随机初始化的权重来创建这些模型。

import torchvision.models as modelsresnet18 = models.resnet18()alexnet = models.alexnet()squeezenet = models.squeezenet1_0()densenet = models.densenet_161()

We provide pre-trained models for the ResNet variants and AlexNet, using the PyTorch torch.utils.model_zoo. These can constructed by passing pretrained=True: 对于ResNet variants和AlexNet，我们也提供了预训练(pre-trained)的模型。

import torchvision.models as models#pretrained=True就可以使用预训练的模型resnet18 = models.resnet18(pretrained=True)alexnet = models.alexnet(pretrained=True)

ImageNet 1-crop error rates (224x224)