diff options
Diffstat (limited to 'modules/textual_inversion/textual_inversion.py')
| -rw-r--r-- | modules/textual_inversion/textual_inversion.py | 14 |
1 files changed, 5 insertions, 9 deletions
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 5421a758..8731ea5d 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -251,6 +251,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat if save_model_every or create_image_every:
assert log_directory, "Log directory is empty"
+
def create_dummy_mask(x, width=None, height=None):
if shared.sd_model.model.conditioning_key in {'hybrid', 'concat'}:
@@ -380,17 +381,12 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ break
with devices.autocast():
- # c = stack_conds(batch.cond).to(devices.device)
- # mask = torch.tensor(batch.emb_index).to(devices.device, non_blocking=pin_memory)
- # print(mask)
- # c[:, 1:1+embedding.vec.shape[0]] = embedding.vec.to(devices.device, non_blocking=pin_memory)
-
-
- if img_c is None:
- img_c = create_dummy_mask(c, training_width, training_height)
-
x = batch.latent_sample.to(devices.device, non_blocking=pin_memory)
c = shared.sd_model.cond_stage_model(batch.cond_text)
+
+ if img_c is None:
+ img_c = create_dummy_mask(c, training_width, training_height)
+
cond = {"c_concat": [img_c], "c_crossattn": [c]}
loss = shared.sd_model(x, cond)[0] / gradient_step
del x
|