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wasserstein-gan
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Merge pull request #37 from eriche2016/patch-1 

compitible with latest pytorch  such that nn.parallel.data_parallel w…
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Soumith Chintala 2017-04-06 01:57:01 -04:00 committed by GitHub
parent 27e72795ad 5ef486cec5
commit ebe4b4ca60
1 changed files with 16 additions and 13 deletions
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29
models/dcgan.py
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@ -44,10 +44,11 @@ class DCGAN_D(nn.Module):
def forward(self, input): def forward(self, input):
gpu_ids = None
if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1: if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
gpu_ids = range(self.ngpu) output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
output = nn.parallel.data_parallel(self.main, input, gpu_ids) else:
output = self.main(input)
output = output.mean(0) output = output.mean(0)
return output.view(1) return output.view(1)
@ -98,11 +99,11 @@ class DCGAN_G(nn.Module):
self.main = main self.main = main
def forward(self, input): def forward(self, input):
gpu_ids = None
if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1: if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
gpu_ids = range(self.ngpu) output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
return nn.parallel.data_parallel(self.main, input, gpu_ids) else:
output = self.main(input)
return output
############################################################################### ###############################################################################
class DCGAN_D_nobn(nn.Module): class DCGAN_D_nobn(nn.Module):
def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0): def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0):
@ -143,10 +144,11 @@ class DCGAN_D_nobn(nn.Module):
def forward(self, input): def forward(self, input):
gpu_ids = None
if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1: if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
gpu_ids = range(self.ngpu) output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
output = nn.parallel.data_parallel(self.main, input, gpu_ids) else:
output = self.main(input)
output = output.mean(0) output = output.mean(0)
return output.view(1) return output.view(1)
@ -190,7 +192,8 @@ class DCGAN_G_nobn(nn.Module):
self.main = main self.main = main
def forward(self, input): def forward(self, input):
gpu_ids = None
if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1: if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
gpu_ids = range(self.ngpu) output = nn.parallel.data_parallel(self.main, input, range(self.ngpu))
return nn.parallel.data_parallel(self.main, input, gpu_ids) else:
output = self.main(input)
return output