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fix the merge

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AUTOMATIC 2023-01-04 17:45:01 +03:00
parent 8839b372bf
commit 184e670126
1 changed files with 5 additions and 9 deletions
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10
modules/textual_inversion/textual_inversion.py
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@ -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: if save_model_every or create_image_every:
assert log_directory, "Log directory is empty" assert log_directory, "Log directory is empty"
def create_dummy_mask(x, width=None, height=None): def create_dummy_mask(x, width=None, height=None):
if shared.sd_model.model.conditioning_key in {'hybrid', 'concat'}: 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 break
with devices.autocast(): with devices.autocast():
# c = stack_conds(batch.cond).to(devices.device) x = batch.latent_sample.to(devices.device, non_blocking=pin_memory)
# mask = torch.tensor(batch.emb_index).to(devices.device, non_blocking=pin_memory) c = shared.sd_model.cond_stage_model(batch.cond_text)
# print(mask)
# c[:, 1:1+embedding.vec.shape[0]] = embedding.vec.to(devices.device, non_blocking=pin_memory)
if img_c is None: if img_c is None:
img_c = create_dummy_mask(c, training_width, training_height) 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)
cond = {"c_concat": [img_c], "c_crossattn": [c]} cond = {"c_concat": [img_c], "c_crossattn": [c]}
loss = shared.sd_model(x, cond)[0] / gradient_step loss = shared.sd_model(x, cond)[0] / gradient_step
del x del x