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fix to work with cfg scale=1

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Kohya S
2023-11-29 12:42:12 +09:00
parent 764e333fa2
commit 39bb319d4c
1 changed files with 7 additions and 4 deletions
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11
sdxl_gen_img.py
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@@ -504,7 +504,8 @@ class PipelineLike:
uncond_embeddings = tes_uncond_embs[0] uncond_embeddings = tes_uncond_embs[0]
for i in range(1, len(tes_text_embs)): for i in range(1, len(tes_text_embs)):
text_embeddings = torch.cat([text_embeddings, tes_text_embs[i]], dim=2) # n,77,2048 text_embeddings = torch.cat([text_embeddings, tes_text_embs[i]], dim=2) # n,77,2048
uncond_embeddings = torch.cat([uncond_embeddings, tes_uncond_embs[i]], dim=2) # n,77,2048 if do_classifier_free_guidance:
uncond_embeddings = torch.cat([uncond_embeddings, tes_uncond_embs[i]], dim=2) # n,77,2048
if do_classifier_free_guidance: if do_classifier_free_guidance:
if negative_scale is None: if negative_scale is None:
@@ -567,9 +568,11 @@ class PipelineLike:
text_pool = clip_vision_embeddings # replace: same as ComfyUI (?) text_pool = clip_vision_embeddings # replace: same as ComfyUI (?)
c_vector = torch.cat([text_pool, c_vector], dim=1) c_vector = torch.cat([text_pool, c_vector], dim=1)
uc_vector = torch.cat([uncond_pool, uc_vector], dim=1) if do_classifier_free_guidance:
uc_vector = torch.cat([uncond_pool, uc_vector], dim=1)
vector_embeddings = torch.cat([uc_vector, c_vector]) vector_embeddings = torch.cat([uc_vector, c_vector])
else:
vector_embeddings = c_vector
# set timesteps # set timesteps
self.scheduler.set_timesteps(num_inference_steps, self.device) self.scheduler.set_timesteps(num_inference_steps, self.device)