use normal tokenizer

This commit is contained in:
smthemex
2025-04-13 21:34:47 +08:00
committed by GitHub
parent 3b876f0364
commit 1fb8de3483
+5 -3
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@@ -976,12 +976,14 @@ class StoryDiffusion_CLIPTextEncode:
else:
boxes = [[[0, 0, 0, 0], [0, 0, 0, 0]]] # used if you want no layout guidance
print(f"Roles position on {boxes}")
from transformers import CLIPTokenizer
tokenizer_=CLIPTokenizer.from_pretrained(os.path.join(dir_path, "local_repo/tokenizer"))
for i in prompts_dual:
phrase_idxes = [get_phrases_idx_cf(clip, phrases[0], i)]
eot_idxes = [[get_eot_idx_cf(clip, i)] * len(phrases[0])]
phrase_idxes = [get_phrases_idx_cf(tokenizer_, phrases[0], i)]
eot_idxes = [[get_eot_idx_cf(tokenizer_, i)] * len(phrases[0])]
cross_attention_kwargs, grounding_kwargs = get_ms_phrase_emb(boxes, device, infer_type_g,
[0], 1, phrase_idxes,
1, eot_idxes, phrases, clip)
1, eot_idxes, phrases, clip,tokenizer_)
daul_emb = cf_clip(prompts_dual, clip, infer_mode,role_list,input_split=False)
else:
daul_emb=cf_clip(prompts_dual, clip, infer_mode,role_list,input_split=False) # maker