| import argparse | |
| import json | |
| from typing import Any | |
| import torch | |
| from .config import ModelConfig | |
| from .model import SupernovaModel | |
| from .tokenizer import load_gpt2_tokenizer | |
| def main(config_path: str): | |
| cfg = ModelConfig.from_json_file(config_path) | |
| tok = load_gpt2_tokenizer() | |
| assert tok.vocab_size == cfg.vocab_size | |
| model = SupernovaModel(cfg) | |
| total_params = sum(p.numel() for p in model.parameters()) | |
| print(json.dumps({ | |
| "vocab_size": tok.vocab_size, | |
| "n_positions": cfg.n_positions, | |
| "d_model": cfg.d_model, | |
| "n_layers": cfg.n_layers, | |
| "n_heads": cfg.n_heads, | |
| "total_params": total_params, | |
| "exact": total_params == 25_000_000 | |
| }, indent=2)) | |
| if __name__ == "__main__": | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--config", required=True) | |
| args = ap.parse_args() | |
| main(args.config) | |