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关于ResNeXt网络的pytorch实现_python_脚本之家
print("Start Training, resnext!") # 定义遍历数据集的次数 with open("/home/dell/Desktop/zhou/train7/acc.txt", "w") as f1: with open("/home/dell/Desktop/zhou/train7/log.txt", "w")as f2: for epoch in range(num_epochs): print('Epoch {}/{}'.format(epoch+1, num_epochs)) prin...
www.jb51.net/article/1783...htm 2024-5-28
浅谈pytorch中的nn.Sequential(*net[3: 5])是啥意思_python_脚本之家
14 1classResNeXt101(nn.Module): 2def__init__(self): 3super(ResNeXt101,self).__init__() 4net=resnext101() # print(os.getcwd(), net) 5net=list(net.children())# net.children()得到resneXt 的表层网络 # for i, value in enumerate(net): # print(i, value) 6self.layer0=nn.Sequenti...
www.jb51.net/article/2106...htm 2024-5-23
简单易懂Pytorch实战实例VGG深度网络_python_脚本之家
# net = ResNeXt29_2x64d() # net = MobileNet() # net = MobileNetV2() # net = DPN92() # net = ShuffleNetG2() # net = SENet18() # 如果GPU可用,使用GPU ifuse_cuda: # move param and buffer to GPU net.cuda() # parallel use GPU ...
www.jb51.net/article/1685...htm 2024-5-31
Python卷积神经网络图片分类框架详解分析_python_脚本之家
# resnet50 resnet101 resnet152 resnext50_32x4d resnext101_32x8d wide_resnet50_2 wide_resnet101_2 # senet154 se_resnet50 se_resnet101 se_resnet152 se_resnext50_32x4d se_resnext101_32x4d # nasnetalarge pnasnet5large # densenet121 densenet161 densenet169 densenet201 # efficientnet-b0 ...
www.jb51.net/article/2274...htm 2024-5-31
pytorch构建多模型实例_python_脚本之家
img_model = pretrainedmodels.__dict__[backbone1](num_classes=1000, pretrained='imagenet') #seresnext101 else: img_model = pretrainedmodels.__dict__[backbone1](num_classes=1000, pretrained=None) self.visit_model=DPN26() self.img_encoder = list(img_model.children())[:-2] self.img_enco...
www.jb51.net/article/1784...htm 2024-5-31