From f8d48917ba25ffe7ca8b9f1c3af25d126112f864 Mon Sep 17 00:00:00 2001 From: Yousef Rafat <81116377+yousef-rafat@users.noreply.github.com> Date: Sat, 6 Sep 2025 01:22:23 +0300 Subject: [PATCH] additional styling --- comfy/ldm/higgsv2/preprocess.py | 6 +++--- comfy/ldm/higgsv2/tokenizer.py | 1 - 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/comfy/ldm/higgsv2/preprocess.py b/comfy/ldm/higgsv2/preprocess.py index 219b5b374..7c9f74789 100644 --- a/comfy/ldm/higgsv2/preprocess.py +++ b/comfy/ldm/higgsv2/preprocess.py @@ -366,13 +366,13 @@ def prepare_chatml_sample(sample: Union[ChatMLSample, Dict], tokenizer): audio_contents.append(content) if role == "user" or role == "system": text_tokens = tokenizer.encode( - f"<|audio_bos|><|AUDIO|><|audio_eos|>", + "<|audio_bos|><|AUDIO|><|audio_eos|>", add_special_tokens=False, ) input_tokens.extend(text_tokens) elif role == "assistant": text_tokens = tokenizer.encode( - f"<|audio_out_bos|><|AUDIO_OUT|><|audio_eos|>", + "<|audio_out_bos|><|AUDIO_OUT|><|audio_eos|>", add_special_tokens=False, ) input_tokens.extend(text_tokens) @@ -587,7 +587,7 @@ class HiggsAudioSampleCollator: # I tried to remove the for-loop in original implementation # but to do batching with padding caused problem so I turned it into a list compre. lengths = [seg.shape[1] for seg in audio_in_ids_l] - aug_lengths = [l + 2 for l in lengths] + aug_lengths = [length + 2 for length in lengths] audio_in_ids_start = torch.cumsum( torch.tensor([0] + aug_lengths[:-1], dtype=torch.long), dim=0 ) diff --git a/comfy/ldm/higgsv2/tokenizer.py b/comfy/ldm/higgsv2/tokenizer.py index d467d23ae..42c01fccc 100644 --- a/comfy/ldm/higgsv2/tokenizer.py +++ b/comfy/ldm/higgsv2/tokenizer.py @@ -1,4 +1,3 @@ -import os import math import torch import torch.nn as nn