JGZYES
28535b1c74
- pmai unified CLI (generate/chat/interactive/http/inspect/output/config) - GPT+MoE transformer, .pap (f32/fp16/q8) + GGUF loader (order+version adaptive) - llama/Mixtral arch: RoPE+GQA+SwiGLU+MoE (C==torch verified) - C llama BPE tokenizer (validated vs llama-cpp-python) - training framework + 0.1B/0.22B MoE models; quantization fp16/q8 - build artifacts to output/; HTTP API; config.yaml; scripts; openapi
45 行
1.3 KiB
Python
45 行
1.3 KiB
Python
# -*- coding: utf-8 -*-
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"""对拍：torch 贪心 vs C 贪心，验证两端数学一致。"""
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from __future__ import annotations
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import argparse
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import subprocess
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import model as model_mod
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import tokenizer as tok
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--pap", required=True)
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ap.add_argument("--prompt", default="First Citizen:")
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ap.add_argument("--n", type=int, default=40)
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ap.add_argument("--cbin", default="/mnt/f/ParlzMAI/build/moe-serve")
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args = ap.parse_args()
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m, vocab, merges = model_mod.load_pap_model(args.pap)
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init = tok.encode(args.prompt, m.cfg["vocab_size"], merges)
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ids = m.generate_from_ids(init, args.n, temperature=0) # greedy
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py_text = tok.decode(ids, vocab)
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out = subprocess.run(
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[args.cbin, "--model", args.pap, "--prompt", args.prompt,
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"--n_tokens", str(args.n), "--temperature", "0", "--top_k", "0"],
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capture_output=True)
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c_all = out.stdout.decode("utf-8", errors="replace")
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idx = c_all.rfind(args.prompt)
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c_text = c_all[idx:] if idx >= 0 else c_all
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print("=== torch greedy ===")
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print(py_text)
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print("=== C greedy ===")
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print(c_text.strip())
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ok = c_text.strip() == py_text.strip()
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print(f"\n[MATCH] {'YES' if ok else 'NO'}")
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return 0 if ok else 1
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if __name__ == "__main__":
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import sys
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sys.exit(main())
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