小编fja*_*faw的帖子

首先，我曾使用过像'model.cuda（）'这样的模型和数据转换为cuda。但是它仍然有这样的问题。我调试模型的每一层，每个模块的权重为iscuda = True。那么有人知道为什么会出现这样的问题吗？

我有两种模型，一种是resnet50，另一种包含第一个作为主干。

class FC_Resnet(nn.Module):
    def __init__(self, model, num_classes):
        super(FC_Resnet, self).__init__()

        # feature encoding
        self.features = nn.Sequential(
            model.conv1,
            model.bn1,
            model.relu,
            model.maxpool,
            model.layer1,
            model.layer2,
            model.layer3,
            model.layer4)

        # classifier
        num_features = model.layer4[1].conv1.in_channels
        self.classifier = nn.Sequential(
            nn.Conv2d(num_features, num_classes, kernel_size=1, bias=True))

    def forward(self, x):
        # children=self.features.children()
        # for child in children:
        #     if child.weight is not None:
        #         print(child.weight.device)
        x = self.features(x)
        x = self.classifier(x)
        return x

def fc_resnet50(num_classes=20, pre_trained=True):
    model = FC_Resnet(models.resnet50(pre_trained), num_classes)

    return model

还有一个：

class PeakResponseMapping(nn.Sequential):
    def __init__(self, *args, **kargs): …