diff options
Diffstat (limited to 'modules/textual_inversion/dataset.py')
| -rw-r--r-- | modules/textual_inversion/dataset.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index f470324a..2dc64c3c 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -82,7 +82,7 @@ class PersonalizedBase(Dataset): torchdata = torch.from_numpy(npimage).permute(2, 0, 1).to(device=device, dtype=torch.float32)
latent_sample = None
- with torch.autocast("cuda"):
+ with devices.autocast():
latent_dist = model.encode_first_stage(torchdata.unsqueeze(dim=0))
if latent_sampling_method == "once" or (latent_sampling_method == "deterministic" and not isinstance(latent_dist, DiagonalGaussianDistribution)):
@@ -101,7 +101,7 @@ class PersonalizedBase(Dataset): entry.cond_text = self.create_text(filename_text)
if include_cond and not (self.tag_drop_out != 0 or self.shuffle_tags):
- with torch.autocast("cuda"):
+ with devices.autocast():
entry.cond = cond_model([entry.cond_text]).to(devices.cpu).squeeze(0)
self.dataset.append(entry)
@@ -117,13 +117,13 @@ class PersonalizedBase(Dataset): def create_text(self, filename_text):
text = random.choice(self.lines)
- text = text.replace("[name]", self.placeholder_token)
tags = filename_text.split(',')
if self.tag_drop_out != 0:
tags = [t for t in tags if random.random() > self.tag_drop_out]
if self.shuffle_tags:
random.shuffle(tags)
text = text.replace("[filewords]", ','.join(tags))
+ text = text.replace("[name]", self.placeholder_token)
return text
def __len__(self):
|