concat network
2020.08.27 00:19
https://discuss.pytorch.org/t/concatenate-layer-output-with-additional-input-data/20462
댓글 3
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WHRIA
2020.09.05 11:08
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WHRIA
2020.09.05 11:17
class MyModelA(nn.Module): def __init__(self): super(MyModelA, self).__init__() self.fc1 = nn.Linear(10, 2) def forward(self, x): x = self.fc1(x) return x class MyModelB(nn.Module): def __init__(self): super(MyModelB, self).__init__() self.fc1 = nn.Linear(20, 2) def forward(self, x): x = self.fc1(x) return x class MyEnsemble(nn.Module): def __init__(self, modelA, modelB): super(MyEnsemble, self).__init__() self.modelA = modelA self.modelB = modelB self.classifier = nn.Linear(4, 2) def forward(self, x1, x2): x1 = self.modelA(x1) x2 = self.modelB(x2) x = torch.cat((x1, x2), dim=1) x = self.classifier(F.relu(x)) return x # Create models and load state_dicts modelA = MyModelA() modelB = MyModelB() # Load state dicts modelA.load_state_dict(torch.load(PATH)) modelB.load_state_dict(torch.load(PATH)) model = MyEnsemble(modelA, modelB) x1, x2 = torch.randn(1, 10), torch.randn(1, 20) output = model(x1, x2)
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WHRIA
2020.10.08 13:08
https://gist.github.com/andrewjong/6b02ff237533b3b2c554701fb53d5c4d
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1545 | faster rcnn resnet 101 | WHRIA | 2018.09.09 | 173 |
1544 | 나이 40에... | WHRIA | 2018.09.01 | 141 |
1543 | letencrypt - win | WHRIA | 2018.08.12 | 47 |
1542 |
달러 환율
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1541 | Interpretation of the Outputs of Deep Learning Model Trained with Skin Cancer Dataset [1] | WHRIA | 2018.06.02 | 7708 |
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1536 | 당좌대월이자율 | WHRIA | 2018.03.06 | 2601 |
1535 | security 0 | WHRIA | 2018.03.02 | 2465 |
https://discuss.pytorch.org/t/combining-trained-models-in-pytorch/28383/2