diff options
| -rw-r--r-- | data/unaligned_dataset.py | 5 | ||||
| -rw-r--r-- | models/networks.py | 4 |
2 files changed, 6 insertions, 3 deletions
diff --git a/data/unaligned_dataset.py b/data/unaligned_dataset.py index c5e5460..ad0c11b 100644 --- a/data/unaligned_dataset.py +++ b/data/unaligned_dataset.py @@ -25,7 +25,10 @@ class UnalignedDataset(BaseDataset): def __getitem__(self, index): A_path = self.A_paths[index % self.A_size] index_A = index % self.A_size - index_B = random.randint(0, self.B_size - 1) + if self.opt.serial_batches: + index_B = index % self.B_size + else: + index_B = random.randint(0, self.B_size - 1) B_path = self.B_paths[index_B] # print('(A, B) = (%d, %d)' % (index_A, index_B)) A_img = Image.open(A_path).convert('RGB') diff --git a/models/networks.py b/models/networks.py index e6e0a87..3c54138 100644 --- a/models/networks.py +++ b/models/networks.py @@ -26,9 +26,9 @@ def weights_init_xavier(m): classname = m.__class__.__name__ # print(classname) if classname.find('Conv') != -1: - init.xavier_normal(m.weight.data, gain=1) + init.xavier_normal(m.weight.data, gain=0.02) elif classname.find('Linear') != -1: - init.xavier_normal(m.weight.data, gain=1) + init.xavier_normal(m.weight.data, gain=0.02) elif classname.find('BatchNorm2d') != -1: init.normal(m.weight.data, 1.0, 0.02) init.constant(m.bias.data, 0.0) |