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Fix ltxav te mem estimation. (#12643)

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comfyanonymous 2026-02-25 20:13:47 -08:00 committed by GitHub
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1 changed files with 5 additions and 2 deletions
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comfy/text_encoders/lt.py
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@ -6,6 +6,7 @@ import comfy.text_encoders.genmo
import torch import torch
import comfy.utils import comfy.utils
import math import math
import itertools
class T5XXLTokenizer(sd1_clip.SDTokenizer): class T5XXLTokenizer(sd1_clip.SDTokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}): def __init__(self, embedding_directory=None, tokenizer_data={}):
@ -199,8 +200,10 @@ class LTXAVTEModel(torch.nn.Module):
constant /= 2.0 constant /= 2.0
token_weight_pairs = token_weight_pairs.get("gemma3_12b", []) token_weight_pairs = token_weight_pairs.get("gemma3_12b", [])
num_tokens = sum(map(lambda a: len(a), token_weight_pairs)) m = min([sum(1 for _ in itertools.takewhile(lambda x: x[0] == 0, sub)) for sub in token_weight_pairs])
num_tokens = max(num_tokens, 64)
num_tokens = sum(map(lambda a: len(a), token_weight_pairs)) - m
num_tokens = max(num_tokens, 642)
return num_tokens * constant * 1024 * 1024 return num_tokens * constant * 1024 * 1024
def ltxav_te(dtype_llama=None, llama_quantization_metadata=None): def ltxav_te(dtype_llama=None, llama_quantization_metadata=None):