SoundGame Dev
f0f0a9b50e
- 共享引擎（app/src/main）：GestureEngine 6 手势识别、AudioEngine 三层音频 （ExoPlayer BGM 交叉淡入 / 对白 ducking / SoundPool 低延迟）、Game/GameEngine 状态机接口、MainActivity 全屏封面 + TalkBack - 《声命线》storyline：末世互动广播剧，3 幕 8 抉择点 4 结局 - 《声东击西》reflex：听声辨位反应，12 波战斗 + BGM 三档 BPM 变速 - 《暗室》escape：3x3 网格密室逃脱，钥匙→铁柜→保险丝→电箱→大门谜题链 - 文档：setup（从零搭建）/ architecture（架构）/ engine-api（引擎 API）/ asset-pipeline（资产流水线）/ games/*（三款游戏设计文档） - 资产管线：Qwen3-TTS 对白 + 程序合成音效/BGM + Mureka BGM 的 gen 脚本与台账， 全部 ogg 资产入库可复现 - env.d 环境脚本：android/tts 入库；sfx/mureka 含密钥不入库，仅提交 .example.sh 模板
91 lines
4.0 KiB
Python
91 lines
4.0 KiB
Python
"""Convert a Stable Audio 3 *-base torch checkpoint → the MLX training npz.
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Torch-free (safetensors.numpy). Produces `dit_<model>-base_f16.npz` — the DiT
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weights + baked conditioner that `lora_train_mlx.py --dit-weights` expects.
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LoRA training uses the BASE checkpoint (not the shipped ARC weights inference
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uses); these npz are auto-downloaded by weights.py, or reproduced here from the
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HF `stabilityai/stable-audio-3-*-base` repos.
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python scripts/export_base_npz.py \
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--base-dir <sa3-*-base> # dir with model.safetensors + model_config.json
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--output models/mlx/dit_<model>-base_f16.npz
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[--validate-against <existing npz>] # assert bit-parity with a known-good npz
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Conversion (identical to the shipped inference-npz layout): strip the DiT
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wrapper prefix `model.model.`, transpose the two Conv1d weights
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[out,in,k]→[out,k,in], rename RMSNorm `.gamma`→`.weight`, remap
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`.to_local_embed.{0,2}`→`.seq.{0,2}`, and fold the 3 conditioner tensors under
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the `cond.` prefix. Same for small (sm-music/sm-sfx) and medium.
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"""
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import argparse
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import mlx.core as mx
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import numpy as np
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from safetensors.numpy import load_file
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_DIT_PREFIX = "model.model."
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_CONV_WEIGHTS = ("preprocess_conv.weight", "postprocess_conv.weight")
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_COND_MAP = {
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"conditioner.conditioners.prompt.padding_embedding": "cond.padding_embedding",
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"conditioner.conditioners.seconds_total.embedder.embedding.1.weight": "cond.seconds_total_weight",
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"conditioner.conditioners.seconds_total.embedder.embedding.1.bias": "cond.seconds_total_bias",
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}
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def convert(base_dir):
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sd = load_file(f"{base_dir}/model.safetensors")
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out = {}
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for k, arr in sd.items():
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if k in _COND_MAP:
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out[_COND_MAP[k]] = mx.array(arr.astype(np.float32))
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continue
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if not k.startswith(_DIT_PREFIX):
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continue # pretransform / T5 backbone — not part of the DiT npz
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sk = k[len(_DIT_PREFIX):]
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a = arr.astype(np.float32)
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if sk in _CONV_WEIGHTS: # Conv1d [out,in,k] -> MLX [out,k,in]
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out[sk] = mx.array(a.transpose(0, 2, 1))
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elif sk.endswith(".gamma"): # RMSNorm .gamma -> .weight
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out[sk[: -len(".gamma")] + ".weight"] = mx.array(a)
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else:
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sk = sk.replace(".to_local_embed.0.", ".to_local_embed.seq.0.")
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sk = sk.replace(".to_local_embed.2.", ".to_local_embed.seq.2.")
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out[sk] = mx.array(a)
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return out
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def main():
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ap = argparse.ArgumentParser(description=__doc__,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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ap.add_argument("--base-dir", required=True)
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ap.add_argument("--output", required=True)
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ap.add_argument("--validate-against", default=None,
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help="Assert key-set + value parity with a known-good npz.")
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args = ap.parse_args()
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wd = convert(args.base_dir)
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print(f"converted {len(wd)} keys ({sum(1 for k in wd if k.startswith('cond'))} conditioner)")
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if args.validate_against:
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ref = dict(mx.load(args.validate_against))
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extra, missing = set(wd) - set(ref), set(ref) - set(wd)
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assert not extra and not missing, f"key mismatch: extra={extra}, missing={missing}"
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worst = max(
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float(mx.max(mx.abs(wd[k].astype(mx.float32) - ref[k].astype(mx.float32))))
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for k in ref
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)
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print(f"validate: {len(ref)} keys match, max|Δ| = {worst:.2e}")
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# Tolerance is fp16-scale: the source ckpt is fp32 and both npz are fp16,
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# so a handful of the specially-transformed keys (conv transpose, the
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# to_local_embed rename) can differ by ~1 fp16 ULP (~4e-3) depending on
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# the rounding path. A real structural bug (wrong transpose/rename) gives
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# an O(0.1-1) diff or a shape/key mismatch — both caught well below this.
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assert worst < 1e-2, "values diverge from the reference npz (structural bug)"
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mx.savez(args.output, **{k: v.astype(mx.float16) for k, v in wd.items()})
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print(f"wrote {args.output}")
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if __name__ == "__main__":
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main()
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