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09ccad2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | """临时调试节点: 导出 CLIP 的 cond embeds 到 models/minimax_h3_adapter/cond_official_ref.npy。
用法（黑屏诊断，插进官方工作流）:
CLIPLoader(官方 qwen3vl-32B GGUF) -> MiniMaxH3ExportCond -> MiniMaxH3ImageToVideo
节点透传 clip 对象（不改变工作流行为），执行时导出 cond npy 并打印路径。
ComfyUI 惰性执行会剪枝无输出节点，故必须输出透传 clip 才能被触发。
"""
import os
import numpy as np
import folder_paths
class MiniMaxH3ExportCond:
@classmethod
def INPUT_TYPES(cls):
return {"required": {
"clip": ("CLIP",),
"prompt": ("STRING", {"default": "a red apple rotating on a wooden table, studio lighting, 3d render",
"multiline": True}),
}}
RETURN_TYPES = ("CLIP",)
RETURN_NAMES = ("clip",)
FUNCTION = "run"
CATEGORY = "model/conditioning/minimax"
def run(self, clip, prompt):
tokens = clip.tokenize(prompt)
cond = clip.encode_from_tokens_scheduled(tokens)
embeds = cond[0][0].float().cpu().numpy()
out_dir = folder_paths.get_folder_paths("minimax_h3_adapter")[0]
os.makedirs(out_dir, exist_ok=True)
path = os.path.join(out_dir, "cond_official_ref.npy")
np.save(path, embeds)
extra = ""
if len(cond[0]) > 1 and isinstance(cond[0][1], dict) and "minimax_token_tags" in cond[0][1]:
tags = cond[0][1]["minimax_token_tags"].cpu().numpy()
extra = f" tags_unique={sorted(set(tags.tolist()))}"
print(f"[export_cond] saved {path} shape={embeds.shape} dtype={embeds.dtype}{extra}", flush=True)
return (clip,)
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