Uploaded sanitized BC250/ROCm Repository.

2026-08-20 00:45:43 +02:00
parent 7d2184f1e8
commit d7d22e93b3
678 changed files with 65963 additions and 1 deletions
@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""Deep engine init diagnostic — catch every failure point."""
+import os, sys, traceback, logging
+from pathlib import Path
+
+# Configure ALL loggers to console
+logging.basicConfig(level=logging.DEBUG, stream=sys.stderr, format='%(name)s %(levelname)s %(message)s')
+
+MODEL_DIR = "/models/qwen3-tts"
+parent = os.path.dirname(os.path.abspath(MODEL_DIR))
+basename = os.path.basename(MODEL_DIR)
+os.chdir(parent)
+print(f"cwd={Path.cwd()}, basename={basename}", flush=True)
+
+project_root = Path.cwd()
+model_dir = project_root / basename
+print(f"model_dir={model_dir}", flush=True)
+
+# Step 1: AssetsManager
+print("\n=== Step 1: AssetsManager ===", flush=True)
+try:
+    from qwen3_tts_gguf.inference.assets import AssetsManager
+    assets = AssetsManager(str(model_dir))
+    print(f"  OK: assets={assets}", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+# Step 2: Tokenizer
+print("\n=== Step 2: Tokenizer ===", flush=True)
+try:
+    from tokenizers import Tokenizer
+    tok = Tokenizer.from_file(str(model_dir / "tokenizer.json"))
+    print(f"  OK: tokenizer loaded", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+# Step 3: CodecEncoder
+print("\n=== Step 3: CodecEncoder ===", flush=True)
+try:
+    from qwen3_tts_gguf.inference.encoder import CodecEncoder
+    codec = CodecEncoder(str(model_dir / "qwen3_tts_codec_encoder.fp16.onnx"))
+    print(f"  OK: codec_encoder={codec}", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+# Step 4: SpeakerEncoder
+print("\n=== Step 4: SpeakerEncoder ===", flush=True)
+try:
+    from qwen3_tts_gguf.inference.encoder import SpeakerEncoder
+    spk = SpeakerEncoder(str(model_dir / "qwen3_tts_speaker_encoder.fp16.onnx"))
+    print(f"  OK: speaker_encoder={spk}", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+# Step 5: DecoderProxy
+print("\n=== Step 5: DecoderProxy ===", flush=True)
+try:
+    from qwen3_tts_gguf.inference.proxy import DecoderProxy
+    decoder = DecoderProxy(str(model_dir / "qwen3_tts_decoder.fp16.onnx"), onnx_provider="CPUExecutionProvider", chunk_size=12)
+    print(f"  OK: decoder={decoder}", flush=True)
+    print("  Waiting for decoder ready (timeout=10)...", flush=True)
+    is_ready = decoder.wait_until_ready(timeout=10)
+    print(f"  decoder ready={is_ready}", flush=True)
+    if hasattr(decoder, 'ready_states'):
+        print(f"  ready_states={decoder.ready_states}", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+# Step 6: LlamaModel
+print("\n=== Step 6: LlamaModel (GGUF) ===", flush=True)
+try:
+    from qwen3_tts_gguf.inference import llama
+    t_path = (model_dir / "qwen3_tts_talker.q5_k.gguf").relative_to(project_root).as_posix()
+    p_path = (model_dir / "qwen3_tts_predictor.q8_0.gguf").relative_to(project_root).as_posix()
+    print(f"  talker_path={t_path}", flush=True)
+    print(f"  predictor_path={p_path}", flush=True)
+    talker = llama.LlamaModel(t_path, n_gpu_layers=-1)
+    print(f"  OK: talker={talker}", flush=True)
+    predictor = llama.LlamaModel(p_path, n_gpu_layers=-1)
+    print(f"  OK: predictor={predictor}", flush=True)
+except Exception as e:
+    print(f"  FAIL: {e}", flush=True)
+    traceback.print_exc()
+
+print("\n=== DONE ===", flush=True)