|  | @@ -1,11 +1,11 @@
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				|  |  |  import torch
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				|  |  | -import torchvision.models as tmodels
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				|  |  | +from torchvision.models import resnet18, ResNet18_Weights
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				|  |  |  import torch.nn as nn
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				|  |  |  
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				|  |  |  class ModelCT(nn.Module):
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				|  |  |      def __init__(self):
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				|  |  |          super(ModelCT, self).__init__()
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				|  |  | -        self.backbone = tmodels.resnet18(pretrained=True)
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				|  |  | +        self.backbone = resnet18(weights=ResNet18_Weights.IMAGENET1K_V1)
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				|  |  |          self.backbone.conv1 = nn.Conv2d(1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
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				|  |  |          self.convolution2d = nn.Conv2d(512, 1, kernel_size=(1, 1), stride=(1, 1), bias=True)
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				|  |  |          self.fc_maxpool = nn.AdaptiveMaxPool2d((1, 1))
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