| """Print the model's internal structure so the ONNX export can be written |
| against real APIs instead of guesses. |
| |
| The original export notebook is gone, and the graphs it produced died with it. |
| Everything downstream (browser bundle, quantization) hangs off being able to |
| re-export, so this dumps the exact callable signatures, module classes and |
| parameter shapes needed to write that exporter once and correctly. |
| |
| Writes /kaggle/working/structure.json and prints a readable summary. |
| """ |
| import inspect |
| import json |
| import sys |
| from pathlib import Path |
|
|
| ROOT = Path("/kaggle/working") |
| REPO = ROOT / "Ming-3.0-tts" |
| MODEL = ROOT / "Ming-3.0-tts-0.5b" |
| OUT = ROOT / "structure.json" |
|
|
|
|
| def describe(name: str, fn) -> dict: |
| try: |
| sig = str(inspect.signature(fn)) |
| except Exception: |
| sig = "<no signature>" |
| return {"name": name, "type": type(fn).__name__, "signature": sig, |
| "doc": (inspect.getdoc(fn) or "")[:400]} |
|
|
|
|
| def main() -> None: |
| import torch |
|
|
| sys.path.insert(0, str(REPO)) |
| for name in ("ming_tts.py", "modeling_bailingmm.py"): |
| p = REPO / name |
| s = p.read_text() |
| s = s.replace("torch_dtype=torch.bfloat16", "torch_dtype=torch.float32") |
| s = s.replace(".eval().to(torch.bfloat16).to(device)", ".eval().to(torch.float32).to(device)") |
| s = s.replace("dtype=torch.bfloat16", "dtype=torch.float32") |
| p.write_text(s) |
|
|
| from ming_tts import MingTTS |
| import tts_tasks |
|
|
| tts = MingTTS(str(MODEL), device="cuda", text_normalization=False) |
| mm = tts.model |
|
|
| info = {"mm_class": type(mm).__name__, "attrs": [a for a in dir(mm) if not a.startswith("_")][:80]} |
|
|
| lm = getattr(mm, "model", None) |
| info["lm_class"] = type(lm).__name__ if lm is not None else None |
| if lm is not None: |
| cfg = getattr(lm, "config", None) |
| info["lm_config"] = {k: v for k, v in vars(cfg).items() |
| if isinstance(v, (int, float, str, bool, list))} if cfg else None |
| info["lm_forward"] = describe("lm.forward", lm.forward) |
|
|
| for attr in ("linear_proj_audio", "prepare_input_embed", "prepare_prompt", "synthesize"): |
| if hasattr(mm, attr): |
| info[attr] = describe(attr, getattr(mm, attr)) |
| if hasattr(tts, attr): |
| info[f"tts.{attr}"] = describe(attr, getattr(tts, attr)) |
|
|
| audio = getattr(mm, "audio", None) |
| info["audio_class"] = type(audio).__name__ if audio is not None else None |
| for m in ("encode", "decode", "quantize", "dequantize"): |
| if audio is not None and hasattr(audio, m): |
| info[f"audio.{m}"] = describe(m, getattr(audio, m)) |
| if audio is not None: |
| cfg = getattr(audio, "config", None) |
| info["audio_config"] = {k: v for k, v in vars(cfg).items() |
| if isinstance(v, (int, float, str, bool))} if cfg else None |
|
|
| flow = getattr(mm, "flowloss", None) |
| info["flow_class"] = type(flow).__name__ if flow is not None else None |
| if flow is not None: |
| info["flow_attrs"] = [a for a in dir(flow) if not a.startswith("_")] |
| dit = getattr(getattr(flow, "cfm", None), "model", None) |
| if dit is not None: |
| info["dit_forward"] = describe("dit.forward", dit.forward) |
|
|
| totals = {} |
| for name, mod in (("lm", lm), ("audio", audio), ("flow", flow)): |
| if mod is not None and hasattr(mod, "parameters"): |
| totals[name] = sum(p.numel() for p in mod.parameters()) |
| if hasattr(mm, "linear_proj_audio") and hasattr(mm.linear_proj_audio, "parameters"): |
| totals["linear_proj_audio"] = sum(p.numel() for p in mm.linear_proj_audio.parameters()) |
| info["param_counts"] = totals |
|
|
| heads = {} |
| for h in ("stop_head", "spk_head", "fc1"): |
| for owner, label in ((mm, f"mm.{h}"), (audio, f"audio.{h}")): |
| if owner is not None and hasattr(owner, h): |
| mod = getattr(owner, h) |
| n = sum(p.numel() for p in mod.parameters()) if hasattr(mod, "parameters") else None |
| heads[label] = n |
| info["heads"] = heads |
|
|
| OUT.write_text(json.dumps(info, ensure_ascii=False, indent=1)) |
| print(json.dumps({k: v for k, v in info.items() if k in |
| ("mm_class", "lm_class", "audio_class", "flow_class", |
| "param_counts", "heads", "lm_config", "audio_config")}, |
| ensure_ascii=False, indent=1)[:4000]) |
| print("\nsignatures:") |
| for k, v in info.items(): |
| if isinstance(v, dict) and "signature" in v: |
| print(f" {k}{v['signature']}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
