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 |
---|---|---|---|---|
1716 | mAP 계산법 | WHRIA | 2019.02.24 | 45558 |
1715 | epitope spreading | han | 2006.05.09 | 40968 |
1714 | encfs | WHRIA | 2020.05.17 | 34162 |
1713 | Heinrich Law (1:29:300 Law) | WHRIA | 2007.08.12 | 24963 |
1712 | 일본 주소 [2] | WHRIA | 2008.06.28 | 24013 |
1711 | 사주팔자 프로그램 | 한승석 | 2003.02.16 | 20304 |
1710 | simple adblock | WHRIA | 2012.04.13 | 18071 |
1709 | 도란사민 | WHRIA | 2011.04.19 | 18067 |
1708 | 탤런트 이윤지씨와 함께 | WHRIA | 2010.02.04 | 17006 |
1707 | penicillin | han | 2003.12.10 | 15672 |
1706 | SSH tunnel | WHRIA | 2007.10.01 | 15078 |
1705 | geexbox [1] | han | 2006.12.01 | 14601 |
1704 | 아이피부과 개원 | WHRIA | 2010.01.18 | 14407 |
1703 | 세무회계 | WHRIA | 2010.01.31 | 14380 |
1702 | 증명사진 | WHRIA | 2010.03.14 | 14308 |
https://discuss.pytorch.org/t/combining-trained-models-in-pytorch/28383/2