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Update bnk_adv_encode.py

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VALADI K JAGANATHAN
2023-11-01 11:44:02 +05:30
committed by GitHub
parent e3674193a6
commit cc54d1d5df
1 changed files with 20 additions and 12 deletions
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py/bnk_adv_encode.py
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@@ -238,17 +238,24 @@ def prepareXL(embs_l, embs_g, pooled, clip_balance):
def advanced_encode(clip, text, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True): def advanced_encode(clip, text, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True):
tokenized = clip.tokenize(text, return_word_ids=True) tokenized = clip.tokenize(text, return_word_ids=True)
if isinstance(clip.cond_stage_model, (SDXLClipModel, SDXLRefinerClipModel, SDXLClipG)): if isinstance(tokenized, dict):
embs_l = None embs_l = None
embs_g = None embs_g = None
pooled = None pooled = None
if 'l' in tokenized and isinstance(clip.cond_stage_model, SDXLClipModel): if 'l' in tokenized:
embs_l, _ = advanced_encode_from_tokens(tokenized['l'], if isinstance(clip.cond_stage_model, SDXLClipModel):
token_normalization, embs_l, _ = advanced_encode_from_tokens(tokenized['l'],
weight_interpretation, token_normalization,
lambda x: encode_token_weights(clip, x, encode_token_weights_l), weight_interpretation,
w_max=w_max, lambda x: encode_token_weights(clip, x, encode_token_weights_l),
return_pooled=False) w_max=w_max,
return_pooled=False)
else:
return advanced_encode_from_tokens(tokenized['l'],
token_normalization,
weight_interpretation,
lambda x: encode_token_weights(clip, x, encode_token_weights_l),
w_max=w_max)
if 'g' in tokenized: if 'g' in tokenized:
embs_g, pooled = advanced_encode_from_tokens(tokenized['g'], embs_g, pooled = advanced_encode_from_tokens(tokenized['g'],
token_normalization, token_normalization,
@@ -259,11 +266,12 @@ def advanced_encode(clip, text, token_normalization, weight_interpretation, w_ma
apply_to_pooled=apply_to_pooled) apply_to_pooled=apply_to_pooled)
return prepareXL(embs_l, embs_g, pooled, clip_balance) return prepareXL(embs_l, embs_g, pooled, clip_balance)
else: else:
return advanced_encode_from_tokens(tokenized['l'], return advanced_encode_from_tokens(tokenized,
token_normalization, token_normalization,
weight_interpretation, weight_interpretation,
lambda x: (clip.encode_from_tokens({'l': x}), None), lambda x: (clip.encode_from_tokens(x), None),
w_max=w_max) w_max=w_max)
def advanced_encode_XL(clip, text1, text2, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True): def advanced_encode_XL(clip, text1, text2, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True):
tokenized1 = clip.tokenize(text1, return_word_ids=True) tokenized1 = clip.tokenize(text1, return_word_ids=True)
tokenized2 = clip.tokenize(text2, return_word_ids=True) tokenized2 = clip.tokenize(text2, return_word_ids=True)