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Print all log messages to stderr instead of stdout

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This commit is contained in:
刘鑫
2026-01-12 15:30:45 +08:00
parent db75a7269b
commit e8dd956fc2
7 changed files with 100 additions and 96 deletions
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42
lora_ft_webui.py
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@ -104,7 +104,7 @@ def get_timestamp_str():
def get_or_load_asr_model():
global asr_model
if asr_model is None:
print("Loading ASR model (SenseVoiceSmall)...")
print("Loading ASR model (SenseVoiceSmall)...", file=sys.stderr)
device = "cuda:0" if torch.cuda.is_available() else "cpu"
asr_model = AutoModel(
model="iic/SenseVoiceSmall",
@ -123,7 +123,7 @@ def recognize_audio(audio_path):
text = res[0]["text"].split('|>')[-1]
return text
except Exception as e:
print(f"ASR Error: {e}")
print(f"ASR Error: {e}", file=sys.stderr)
return ""
def scan_lora_checkpoints(root_dir="lora", with_info=False):
@ -181,7 +181,7 @@ def load_lora_config_from_checkpoint(lora_path):
if lora_cfg_dict:
return LoRAConfig(**lora_cfg_dict), lora_info.get("base_model")
except Exception as e:
print(f"Warning: Failed to load lora_config.json: {e}")
print(f"Warning: Failed to load lora_config.json: {e}", file=sys.stderr)
return None, None
def get_default_lora_config():
@ -197,7 +197,7 @@ def get_default_lora_config():
def load_model(pretrained_path, lora_path=None):
global current_model
print(f"Loading model from {pretrained_path}...")
print(f"Loading model from {pretrained_path}...", file=sys.stderr)
lora_config = None
lora_weights_path = None
@ -209,11 +209,11 @@ def load_model(pretrained_path, lora_path=None):
# Try to load LoRA config from lora_config.json
lora_config, _ = load_lora_config_from_checkpoint(full_lora_path)
if lora_config:
print(f"Loaded LoRA config from {full_lora_path}/lora_config.json")
print(f"Loaded LoRA config from {full_lora_path}/lora_config.json", file=sys.stderr)
else:
# Fallback to default config for old checkpoints
lora_config = get_default_lora_config()
print("Using default LoRA config (lora_config.json not found)")
print("Using default LoRA config (lora_config.json not found)", file=sys.stderr)
# Always init with a default LoRA config to allow hot-swapping later
if lora_config is None:
@ -251,36 +251,36 @@ def run_inference(text, prompt_wav, prompt_text, lora_selection, cfg_scale, step
# 优先使用保存的 base_model 路径
if os.path.exists(saved_base_model):
base_model_path = saved_base_model
print(f"Using base model from LoRA config: {base_model_path}")
print(f"Using base model from LoRA config: {base_model_path}", file=sys.stderr)
else:
print(f"Warning: Saved base_model path not found: {saved_base_model}")
print(f"Falling back to default: {base_model_path}")
print(f"Warning: Saved base_model path not found: {saved_base_model}", file=sys.stderr)
print(f"Falling back to default: {base_model_path}", file=sys.stderr)
except Exception as e:
print(f"Warning: Failed to read base_model from LoRA config: {e}")
print(f"Warning: Failed to read base_model from LoRA config: {e}", file=sys.stderr)
# 加载模型
try:
print(f"Loading base model: {base_model_path}")
print(f"Loading base model: {base_model_path}", file=sys.stderr)
status_msg = load_model(base_model_path)
if lora_selection and lora_selection != "None":
print(f"Model loaded for LoRA: {lora_selection}")
print(f"Model loaded for LoRA: {lora_selection}", file=sys.stderr)
except Exception as e:
error_msg = f"Failed to load model from {base_model_path}: {str(e)}"
print(error_msg)
print(error_msg, file=sys.stderr)
return None, error_msg
# Handle LoRA hot-swapping
if lora_selection and lora_selection != "None":
full_lora_path = os.path.join("lora", lora_selection)
print(f"Hot-loading LoRA: {full_lora_path}")
print(f"Hot-loading LoRA: {full_lora_path}", file=sys.stderr)
try:
current_model.load_lora(full_lora_path)
current_model.set_lora_enabled(True)
except Exception as e:
print(f"Error loading LoRA: {e}")
print(f"Error loading LoRA: {e}", file=sys.stderr)
return None, f"Error loading LoRA: {e}"
else:
print("Disabling LoRA")
print("Disabling LoRA", file=sys.stderr)
current_model.set_lora_enabled(False)
if seed != -1:
@ -297,11 +297,11 @@ def run_inference(text, prompt_wav, prompt_text, lora_selection, cfg_scale, step
# 如果没有提供参考文本，尝试自动识别
if not prompt_text or not prompt_text.strip():
print("参考音频已提供但缺少文本，自动识别中...")
print("参考音频已提供但缺少文本，自动识别中...", file=sys.stderr)
try:
final_prompt_text = recognize_audio(prompt_wav)
if final_prompt_text:
print(f"自动识别文本: {final_prompt_text}")
print(f"自动识别文本: {final_prompt_text}", file=sys.stderr)
else:
return None, "错误：无法识别参考音频内容，请手动填写参考文本"
except Exception as e:
@ -1114,12 +1114,12 @@ with gr.Blocks(
choices = ["None"] + [ckpt[0] for ckpt in checkpoints_with_info]
# 输出调试信息
print(f"刷新 LoRA 列表: 找到 {len(checkpoints_with_info)} 个检查点")
print(f"刷新 LoRA 列表: 找到 {len(checkpoints_with_info)} 个检查点", file=sys.stderr)
for ckpt_path, base_model in checkpoints_with_info:
if base_model:
print(f" - {ckpt_path} (Base Model: {base_model})")
print(f" - {ckpt_path} (Base Model: {base_model})", file=sys.stderr)
else:
print(f" - {ckpt_path}")
print(f" - {ckpt_path}", file=sys.stderr)
return gr.update(choices=choices, value="None")