Fabian
69 lines
2.7 KiB
Python
69 lines
2.7 KiB
Python
"""Test DecoderProxy from proxy.py and full engine init with exception details"""
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import sys, os, time, traceback
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os.chdir("/models")
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sys.path.insert(0, "/opt/qwen3-tts")
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os.environ["PYTHONUNBUFFERED"] = "1"
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print("=== Test DecoderProxy from proxy.py ===", flush=True)
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try:
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from qwen3_tts_gguf.inference.proxy import DecoderProxy
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t0 = time.time()
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dec = DecoderProxy(
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"/models/qwen3-tts/qwen3_tts_decoder.fp16.onnx",
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onnx_provider="CPUExecutionProvider",
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chunk_size=2048
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)
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print(f" Constructor OK: {time.time()-t0:.2f}s", flush=True)
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print(f" Waiting for ready (25s)...", flush=True)
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ready = dec.wait_until_ready(timeout=25)
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print(f" ready={ready}", flush=True)
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if hasattr(dec, 'ready_states'):
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print(f" states: {dec.ready_states}", flush=True)
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except Exception as e:
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print(f" FAIL: {e}", flush=True)
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traceback.print_exc()
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print("\n=== Test GGUF loading ===", flush=True)
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try:
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from qwen3_tts_gguf.inference import llama
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t0 = time.time()
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talker = llama.LlamaModel("qwen3-tts/qwen3_tts_talker.q5_k.gguf", n_gpu_layers=-1)
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print(f" Talker OK: {time.time()-t0:.2f}s", flush=True)
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predictor = llama.LlamaModel("qwen3-tts/qwen3_tts_predictor.q8_0.gguf", n_gpu_layers=-1)
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print(f" Predictor OK", flush=True)
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except Exception as e:
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print(f" FAIL: {e}", flush=True)
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traceback.print_exc()
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print("\n=== Full Engine (verbose, catch exception) ===", flush=True)
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try:
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# Monkey-patch to see the actual exception
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import qwen3_tts_gguf.inference.engine as eng_mod
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orig_init = eng_mod.TTSEngine.__init__
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def patched_init(self, *args, **kwargs):
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try:
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orig_init(self, *args, **kwargs)
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except Exception as e:
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print(f" !! Engine __init__ exception: {e}", flush=True)
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traceback.print_exc()
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raise
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eng_mod.TTSEngine.__init__ = patched_init
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from qwen3_tts_gguf.inference import TTSEngine
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t0 = time.time()
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engine = TTSEngine(model_dir="qwen3-tts", onnx_provider="CPUExecutionProvider")
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elapsed = time.time() - t0
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print(f" Engine: ready={engine.ready}, took {elapsed:.2f}s", flush=True)
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print(f" has talker_model: {hasattr(engine, 'talker_model')}", flush=True)
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print(f" has predictor_model: {hasattr(engine, 'predictor_model')}", flush=True)
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print(f" has decoder: {hasattr(engine, 'decoder')}", flush=True)
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if hasattr(engine, 'decoder'):
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print(f" decoder type: {type(engine.decoder)}", flush=True)
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if hasattr(engine.decoder, 'ready_states'):
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print(f" decoder states: {engine.decoder.ready_states}", flush=True)
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except Exception as e:
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print(f" FAIL: {e}", flush=True)
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traceback.print_exc()
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print("\n=== DONE ===", flush=True)
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