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Add CPU option (fix issue #23) #24

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Add CPU option (fix issue #23) #24

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23 changes: 15 additions & 8 deletions code/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -357,21 +357,24 @@ def sampling(self, split_dir):
else:
netG = G_NET()
netG.apply(weights_init)
netG.cuda()
if cfg.CUDA:
netG.cuda()
netG.eval()
#
text_encoder = RNN_ENCODER(self.n_words, nhidden=cfg.TEXT.EMBEDDING_DIM)
state_dict = \
torch.load(cfg.TRAIN.NET_E, map_location=lambda storage, loc: storage)
text_encoder.load_state_dict(state_dict)
print('Load text encoder from:', cfg.TRAIN.NET_E)
text_encoder = text_encoder.cuda()
if cfg.CUDA:
text_encoder = text_encoder.cuda()
text_encoder.eval()

batch_size = self.batch_size
nz = cfg.GAN.Z_DIM
noise = Variable(torch.FloatTensor(batch_size, nz), volatile=True)
noise = noise.cuda()
if cfg.CUDA:
noise = noise.cuda()

model_dir = cfg.TRAIN.NET_G
state_dict = \
Expand Down Expand Up @@ -440,7 +443,8 @@ def gen_example(self, data_dic):
torch.load(cfg.TRAIN.NET_E, map_location=lambda storage, loc: storage)
text_encoder.load_state_dict(state_dict)
print('Load text encoder from:', cfg.TRAIN.NET_E)
text_encoder = text_encoder.cuda()
if cfg.CUDA:
text_encoder = text_encoder.cuda()
text_encoder.eval()

# the path to save generated images
Expand All @@ -454,7 +458,8 @@ def gen_example(self, data_dic):
torch.load(model_dir, map_location=lambda storage, loc: storage)
netG.load_state_dict(state_dict)
print('Load G from: ', model_dir)
netG.cuda()
if cfg.CUDA:
netG.cuda()
netG.eval()
for key in data_dic:
save_dir = '%s/%s' % (s_tmp, key)
Expand All @@ -466,11 +471,13 @@ def gen_example(self, data_dic):
captions = Variable(torch.from_numpy(captions), volatile=True)
cap_lens = Variable(torch.from_numpy(cap_lens), volatile=True)

captions = captions.cuda()
cap_lens = cap_lens.cuda()
if cfg.CUDA:
captions = captions.cuda()
cap_lens = cap_lens.cuda()
for i in range(1): # 16
noise = Variable(torch.FloatTensor(batch_size, nz), volatile=True)
noise = noise.cuda()
if cfg.CUDA:
noise = noise.cuda()
#######################################################
# (1) Extract text embeddings
######################################################
Expand Down