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 |
---|---|---|---|---|
274 | slide note 삭제 슬라이드 노트 삭제 | WHRIA | 2018.09.12 | 4436 |
273 | Deep learning 기반 DEMO | WHRIA | 2018.09.16 | 7121 |
272 | register | WHRIA | 2018.09.21 | 1931 |
271 | ambient-light-sensor | WHRIA | 2018.09.29 | 280 |
270 | Intro | WHRIA | 2018.10.01 | 4081 |
269 | faster rcnn cuda 10 | WHRIA | 2018.10.06 | 2107 |
268 | delayed network drive connect | WHRIA | 2018.10.07 | 152 |
267 | mixed precision training [1] | WHRIA | 2018.11.06 | 1780 |
266 | excel 에서 소수점 표시 함수 | WHRIA | 2018.11.08 | 200 |
265 | ac-68u dd-wrt 에서 정펌으로 복구 | WHRIA | 2018.11.22 | 548 |
264 | fatal error: turbojpeg.h: No such file or directory | WHRIA | 2018.11.24 | 645 |
263 | CNN Models | WHRIA | 2018.12.23 | 353 |
262 | imbalanced dataset | WHRIA | 2018.12.26 | 44 |
261 | center % crop | WHRIA | 2018.12.27 | 71 |
260 | Swap file add | WHRIA | 2019.01.02 | 2132 |
https://discuss.pytorch.org/t/combining-trained-models-in-pytorch/28383/2