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[pull] master from Comfy-Org:master #637

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Merged
pull merged 3 commits into from
Feb 26, 2026
Merged

[pull] master from Comfy-Org:master #637

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eb8737d
Update requirements.txt (#12642)
christian-byrne Feb 26, 2026
e14b044
Fix LTXAV text enc min length. (#12640)
comfyanonymous Feb 26, 2026
7253531
Fix ltxav te mem estimation. (#12643)
comfyanonymous Feb 26, 2026
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9 changes: 6 additions & 3 deletions comfy/text_encoders/lt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import torch
import comfy.utils
import math
import itertools

class T5XXLTokenizer(sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}):
Expand Down Expand Up @@ -72,7 +73,7 @@ class Gemma3_12BTokenizer(Gemma3_Tokenizer, sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}):
tokenizer = tokenizer_data.get("spiece_model", None)
special_tokens = {"<image_soft_token>": 262144, "<end_of_turn>": 106}
super().__init__(tokenizer, pad_with_end=False, embedding_size=3840, embedding_key='gemma3_12b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=512, pad_left=True, disable_weights=True, tokenizer_args={"add_bos": True, "add_eos": False, "special_tokens": special_tokens}, tokenizer_data=tokenizer_data)
super().__init__(tokenizer, pad_with_end=False, embedding_size=3840, embedding_key='gemma3_12b', tokenizer_class=SPieceTokenizer, has_end_token=False, pad_to_max_length=False, max_length=99999999, min_length=1024, pad_left=True, disable_weights=True, tokenizer_args={"add_bos": True, "add_eos": False, "special_tokens": special_tokens}, tokenizer_data=tokenizer_data)


class LTXAVGemmaTokenizer(sd1_clip.SD1Tokenizer):
Expand Down Expand Up @@ -199,8 +200,10 @@ def memory_estimation_function(self, token_weight_pairs, device=None):
constant /= 2.0

token_weight_pairs = token_weight_pairs.get("gemma3_12b", [])
num_tokens = sum(map(lambda a: len(a), token_weight_pairs))
num_tokens = max(num_tokens, 64)
m = min([sum(1 for _ in itertools.takewhile(lambda x: x[0] == 0, sub)) for sub in token_weight_pairs])

num_tokens = sum(map(lambda a: len(a), token_weight_pairs)) - m
num_tokens = max(num_tokens, 642)
return num_tokens * constant * 1024 * 1024

def ltxav_te(dtype_llama=None, llama_quantization_metadata=None):
Expand Down
2 changes: 1 addition & 1 deletion requirements.txt
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@@ -1,4 +1,4 @@
comfyui-frontend-package==1.39.16
comfyui-frontend-package==1.39.19
comfyui-workflow-templates==0.9.3
comfyui-embedded-docs==0.4.3
torch
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