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
69 lines
3.9 KiB
Python
69 lines
3.9 KiB
Python
#!/usr/bin/env python3
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"""Build a SA3 encoder/decoder tier engine with a WIDE dynamic profile.
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python build_tiers.py <tier.onnx> <out.trt> --arch {same-s,same-l} --kind {enc,dec} [--fp8]
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Why "wide": the historical [32,4096]-frame profile was a conservative default, not a model limit.
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With min=1 the models are correct at L=1..31 (verified vs eager — these can't be chunked), and long
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files run natively (a ~12:40 decode / 6:20 encode is a single call, no chunking). See README.
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Profiles built here:
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decoder : latent (1,256,1) .. (1,256,1292) .. (1,256,8192) # 1 frame .. ~12:40
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encoder : audio (1,2,1) .. (1,2,2097152) .. (1,2,33554432) # 1 samp .. ~12:40
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SAME-S -> weakly-typed EXPLICIT_BATCH + BF16 (+ FP8 builder flag for fp8/fp8_fast tiers).
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SAME-L -> strongly-typed + diff_attn_swa plugin + NO FP8 flag (the in-graph fp8 QDQ nodes
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carry the precision). Plugin impl is chosen by GPU arch: AOT on sm_120 (JIT isn't
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stream-capturable there), JIT on sm_90 (override with SA3_SWA_PLUGIN=aot|jit).
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`--fp8` is required for fp8 / fp8_fast SAME-S tiers; harmless/ignored for SAME-L and w8/bf16.
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"""
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import argparse, os, sys
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "scripts"))
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import tensorrt as trt
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DEC_PROFILE = ((1, 256, 1), (1, 256, 1292), (1, 256, 8192))
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ENC_PROFILE = ((1, 2, 1), (1, 2, 2097152), (1, 2, 33554432))
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def build(onnx_path, out_path, arch, kind, fp8):
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lg = trt.Logger(trt.Logger.ERROR)
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trt.init_libnvinfer_plugins(lg, "")
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strong = arch == "same-l"
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flags = 0
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if strong:
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# SWA plugin: sm_120 (Blackwell) needs AOT — the JIT impl isn't stream-capturable there
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# and silently drops the decode inside the runtime's mega-graph. sm_90 uses JIT. Choose by
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# the GPU arch (override with SA3_SWA_PLUGIN=aot|jit); set it before importing the plugin.
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import torch
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gpu = "sm_%d%d" % torch.cuda.get_device_capability()
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want_aot = gpu == "sm_120" or os.environ.get("SA3_SWA_PLUGIN") == "aot"
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os.environ.setdefault("SA3_SWA_PLUGIN", "aot" if want_aot else "jit")
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import diff_attn_nocast_plugin # registers samel::diff_attn_swa (AOT + JIT impls) # noqa: F401
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flags |= 1 << int(trt.NetworkDefinitionCreationFlag.STRONGLY_TYPED)
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flags |= 1 << int(trt.NetworkDefinitionCreationFlag.PREFER_AOT_PYTHON_PLUGINS if want_aot
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else trt.NetworkDefinitionCreationFlag.PREFER_JIT_PYTHON_PLUGINS)
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else:
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flags |= 1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH)
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b = trt.Builder(lg); net = b.create_network(flags); p = trt.OnnxParser(net, lg)
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if not p.parse_from_file(onnx_path):
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for i in range(p.num_errors): print(p.get_error(i))
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raise SystemExit("parse failed")
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cfg = b.create_builder_config(); cfg.set_memory_pool_limit(trt.MemoryPoolType.WORKSPACE, 20 << 30)
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if not strong:
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cfg.set_flag(trt.BuilderFlag.BF16)
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if fp8: cfg.set_flag(trt.BuilderFlag.FP8) # SAME-L carries fp8 in-graph; only SAME-S needs the flag
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name, prof = ("audio", ENC_PROFILE) if kind == "enc" else ("latent", DEC_PROFILE)
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pr = b.create_optimization_profile(); pr.set_shape(name, *prof); cfg.add_optimization_profile(pr)
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ser = b.build_serialized_network(net, cfg)
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if ser is None: raise SystemExit("build failed")
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with open(out_path, "wb") as f: f.write(ser)
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print(f"built {out_path} ({ser.nbytes/1e6:.0f} MB) — {arch} {kind} {'fp8 ' if fp8 else ''}wide", flush=True)
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if __name__ == "__main__":
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ap = argparse.ArgumentParser()
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ap.add_argument("onnx"); ap.add_argument("out")
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ap.add_argument("--arch", required=True, choices=["same-s", "same-l"])
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ap.add_argument("--kind", required=True, choices=["enc", "dec"])
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ap.add_argument("--fp8", action="store_true", help="required for SAME-S fp8/fp8_fast tiers")
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a = ap.parse_args()
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build(a.onnx, a.out, a.arch, a.kind, a.fp8)
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