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
번호 | 제목 | 글쓴이 | 날짜 | 조회 수 |
---|---|---|---|---|
1819 | mAP 계산법 | WHRIA | 2019.02.24 | 45576 |
1818 | epitope spreading | han | 2006.05.09 | 41030 |
1817 | encfs | WHRIA | 2020.05.17 | 35990 |
1816 | Heinrich Law (1:29:300 Law) | WHRIA | 2007.08.12 | 25000 |
1815 | 일본 주소 [2] | WHRIA | 2008.06.28 | 24030 |
1814 |
사주팔자 프로그램
![]() | 한승석 | 2003.02.16 | 20335 |
1813 |
simple adblock
![]() | WHRIA | 2012.04.13 | 18115 |
1812 | 도란사민 | WHRIA | 2011.04.19 | 18102 |
1811 |
탤런트 이윤지씨와 함께
![]() | WHRIA | 2010.02.04 | 17046 |
1810 | penicillin | han | 2003.12.10 | 15717 |
1809 | SSH tunnel | WHRIA | 2007.10.01 | 15087 |
1808 | geexbox [1] | han | 2006.12.01 | 14611 |
1807 | 아이피부과 개원 | WHRIA | 2010.01.18 | 14441 |
1806 | 세무회계 | WHRIA | 2010.01.31 | 14404 |
1805 | 증명사진 | WHRIA | 2010.03.14 | 14335 |
https://discuss.pytorch.org/t/combining-trained-models-in-pytorch/28383/2