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51 lines
2.3 KiB
51 lines
2.3 KiB
7 years ago
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"""DANN model."""
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import torch.nn as nn
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from functions import ReverseLayerF
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class CNNModel(nn.Module):
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def __init__(self):
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super(CNNModel, self).__init__()
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self.restored = False
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self.feature = nn.Sequential()
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self.feature.add_module('f_conv1', nn.Conv2d(1, 64, kernel_size=5))
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self.feature.add_module('f_bn1', nn.BatchNorm2d(64))
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self.feature.add_module('f_pool1', nn.MaxPool2d(2))
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self.feature.add_module('f_relu1', nn.ReLU(True))
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self.feature.add_module('f_conv2', nn.Conv2d(64, 50, kernel_size=5))
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self.feature.add_module('f_bn2', nn.BatchNorm2d(50))
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self.feature.add_module('f_drop1', nn.Dropout2d())
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self.feature.add_module('f_pool2', nn.MaxPool2d(2))
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self.feature.add_module('f_relu2', nn.ReLU(True))
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self.class_classifier = nn.Sequential()
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self.class_classifier.add_module('c_fc1', nn.Linear(50 * 4 * 4, 100))
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self.class_classifier.add_module('c_bn1', nn.BatchNorm2d(100))
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self.class_classifier.add_module('c_relu1', nn.ReLU(True))
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self.class_classifier.add_module('c_drop1', nn.Dropout2d())
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self.class_classifier.add_module('c_fc2', nn.Linear(100, 100))
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self.class_classifier.add_module('c_bn2', nn.BatchNorm2d(100))
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self.class_classifier.add_module('c_relu2', nn.ReLU(True))
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self.class_classifier.add_module('c_fc3', nn.Linear(100, 10))
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self.class_classifier.add_module('c_softmax', nn.LogSoftmax(dim=1))
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self.domain_classifier = nn.Sequential()
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self.domain_classifier.add_module('d_fc1', nn.Linear(50 * 4 * 4, 100))
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self.domain_classifier.add_module('d_bn1', nn.BatchNorm2d(100))
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self.domain_classifier.add_module('d_relu1', nn.ReLU(True))
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self.domain_classifier.add_module('d_fc2', nn.Linear(100, 2))
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self.domain_classifier.add_module('d_softmax', nn.LogSoftmax(dim=1))
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def forward(self, input_data, alpha):
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input_data = input_data.expand(input_data.data.shape[0], 1, 28, 28)
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feature = self.feature(input_data)
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feature = feature.view(-1, 50 * 4 * 4)
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reverse_feature = ReverseLayerF.apply(feature, alpha)
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class_output = self.class_classifier(feature)
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domain_output = self.domain_classifier(reverse_feature)
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return class_output, domain_output
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