vgg16_bn-6c64b313.pth 人工智能 - 深度学习 Ed**离殇上传490.26 MB文件格式zip bn (0)踩踩(0) 所需:15积分
import torchvision.models as models vgg = models.vgg16_bn() pre=torch.load('./vgg16_bn-6c64b313.pth') vgg.load_state_dict(pre) normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],#这是imagenet數據集的均值 std=[0.229, 0.224, 0.225]) tran=transforms.Compose([ transforms.Resize...
firstconv_output_c = inverted_residual_setting[0].input_c # 获取第1个卷积层输出的channel,它对应着第1个bneck的input channel # 定义第1个卷积层,对应参数列表第1行 layers.append(ConvBNActivation(3, # 使用rgb图像,故输入channel为3 firstconv_output_c, # 输出channel为下面第2行对应的第1个bneck...
dcbb9e9d.pth, v 11_ bn: https://download.pytorch.or /models/v 11_ bn-6002323d.pth, v 13_ bn: https://download.pytorch.or /models/v 13_ bn-abd245e5.pth, v 16_ bn: https://download.pytorch.or /models/v 16_ bn-6c64b313.pth, v 19_ bn: https://download.pytorch.or /...
这是因为应该使用的结构是vgg16_bn的结构,否则就没有bn层,改模型为https://download.pytorch.org/models/vgg16_bn-6c64b313.pth 又报错: Traceback (most recent call last): File"./run/vgg16/vgg16_prune_demo.py", line137,in <module>run() ...