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https://github.com/jamiepine/voicebox.git
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fix: load model into local var before patching to avoid half-initialised state
Apply local-var-then-assign pattern to chatterbox_backend.py (multilingual) to match the turbo backend. Also use _current_model_size fallback in unload, delete, and status endpoints for consistent Qwen model size checks.
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@@ -154,6 +154,8 @@ class ChatterboxTurboTTSBackend:
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# Monkey-patch torch.load for CPU loading. The model's .pt files
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# were saved on CUDA; from_local() doesn't pass map_location
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# so loading on CPU fails without this.
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# Load into a local var, apply patches, then publish to
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# self.model so a failed patch doesn't leave us half-initialised.
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if device == "cpu":
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_orig_torch_load = torch.load
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@@ -164,13 +166,13 @@ class ChatterboxTurboTTSBackend:
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with ChatterboxTurboTTSBackend._load_lock:
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torch.load = _patched_load
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try:
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self.model = ChatterboxTurboTTS.from_local(
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model = ChatterboxTurboTTS.from_local(
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local_path, device,
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)
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finally:
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torch.load = _orig_torch_load
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else:
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self.model = ChatterboxTurboTTS.from_local(
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model = ChatterboxTurboTTS.from_local(
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local_path, device,
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)
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@@ -191,7 +193,7 @@ class ChatterboxTurboTTSBackend:
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import types
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# Patch S3Tokenizer (used by s3gen.tokenizer)
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_tokzr = self.model.s3gen.tokenizer
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_tokzr = model.s3gen.tokenizer
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_orig_log_mel = _tokzr.log_mel_spectrogram.__func__
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def _f32_log_mel(self_tokzr, audio, padding=0):
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@@ -203,7 +205,7 @@ class ChatterboxTurboTTSBackend:
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_tokzr.log_mel_spectrogram = types.MethodType(_f32_log_mel, _tokzr)
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# Patch VoiceEncoder
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_ve = self.model.ve
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_ve = model.ve
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_orig_ve_forward = _ve.forward.__func__
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def _f32_ve_forward(self_ve, mels):
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@@ -211,6 +213,9 @@ class ChatterboxTurboTTSBackend:
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_ve.forward = types.MethodType(_f32_ve_forward, _ve)
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# Only publish after all patches succeed
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self.model = model
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logger.info("Chatterbox Turbo TTS loaded successfully")
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except ImportError as e:
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