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Bug Fix #1015

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Ensure custom config hashable in
This commit is contained in:
SWivid
2025-05-05 03:55:05 +08:00
parent 3d969bf78d
commit dad398c0c1
1 changed files with 6 additions and 4 deletions
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src/f5_tts/infer/infer_gradio.py
+6 -4
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@@ -80,6 +80,8 @@ def load_custom(ckpt_path: str, vocab_path="", model_cfg=None):
vocab_path = str(cached_path(vocab_path))
if model_cfg is None:
model_cfg = json.loads(DEFAULT_TTS_MODEL_CFG[2])
elif isinstance(model_cfg, str):
model_cfg = json.loads(model_cfg)
return load_model(DiT, model_cfg, ckpt_path, vocab_file=vocab_path)
@@ -124,7 +126,7 @@ def load_text_from_file(file):
return gr.update(value=text)
@lru_cache(maxsize=100)
@lru_cache(maxsize=100) # NOTE. need to ensure params of infer() hashable
@gpu_decorator
def infer(
ref_audio_orig,
@@ -163,7 +165,7 @@ def infer(
show_info("Loading E2-TTS model...")
E2TTS_ema_model = load_e2tts()
ema_model = E2TTS_ema_model
elif isinstance(model, list) and model[0] == "Custom":
elif isinstance(model, tuple) and model[0] == "Custom":
assert not USING_SPACES, "Only official checkpoints allowed in Spaces."
global custom_ema_model, pre_custom_path
if pre_custom_path != model[1]:
@@ -959,7 +961,7 @@ If you're having issues, try converting your reference audio to WAV or MP3, clip
global tts_model_choice
if new_choice == "Custom": # override in case webpage is refreshed
custom_ckpt_path, custom_vocab_path, custom_model_cfg = load_last_used_custom()
tts_model_choice = ["Custom", custom_ckpt_path, custom_vocab_path, json.loads(custom_model_cfg)]
tts_model_choice = ("Custom", custom_ckpt_path, custom_vocab_path, custom_model_cfg)
return (
gr.update(visible=True, value=custom_ckpt_path),
gr.update(visible=True, value=custom_vocab_path),
@@ -971,7 +973,7 @@ If you're having issues, try converting your reference audio to WAV or MP3, clip
def set_custom_model(custom_ckpt_path, custom_vocab_path, custom_model_cfg):
global tts_model_choice
tts_model_choice = ["Custom", custom_ckpt_path, custom_vocab_path, json.loads(custom_model_cfg)]
tts_model_choice = ("Custom", custom_ckpt_path, custom_vocab_path, custom_model_cfg)
with open(last_used_custom, "w", encoding="utf-8") as f:
f.write(custom_ckpt_path + "\n" + custom_vocab_path + "\n" + custom_model_cfg + "\n")