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enable creating embedding with --medvram

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AUTOMATIC 2022-10-26 09:44:02 +03:00
parent ee73341f04
commit cbb857b675
1 changed files with 3 additions and 0 deletions
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modules/textual_inversion/textual_inversion.py
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@ -157,6 +157,9 @@ def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'):
cond_model = shared.sd_model.cond_stage_model cond_model = shared.sd_model.cond_stage_model
embedding_layer = cond_model.wrapped.transformer.text_model.embeddings embedding_layer = cond_model.wrapped.transformer.text_model.embeddings
with devices.autocast():
cond_model([""]) # will send cond model to GPU if lowvram/medvram is active
ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"] ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"]
embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0) embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0)
vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device) vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device)