| """Generacja melodii z wytrenowanego GPT (wczytuje checkpoint).""" |
| import os, sys |
| import torch |
| sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
| from core.gpt import GPT |
|
|
| sys.stdout.reconfigure(encoding="utf-8") |
| device = "cuda" if torch.cuda.is_available() else "cpu" |
| ck = torch.load("data/models/jig_ckpt.pt", map_location=device, weights_only=False) |
| stoi, itos, cfg = ck["stoi"], ck["itos"], ck["config"] |
|
|
| model = GPT(cfg).to(device) |
| model.load_state_dict(ck["model"]) |
| model.eval() |
| print(f"wczytano GPT ({model.num_params():,} param) | val loss {ck['val_loss']:.3f}") |
|
|
| def gen(seed, n_new=400, temp=0.8, top_k=20): |
| idx = torch.tensor([[stoi[c] for c in seed]], dtype=torch.long, device=device) |
| out = model.generate(idx, n_new, temperature=temp, top_k=top_k)[0].tolist() |
| return "".join(itos[i] for i in out) |
|
|
| seed = "X:1\nM:6/8\nK:D\n" |
| raw = gen(seed, n_new=500, temp=0.8, top_k=20) |
| |
| tunes, cur = [], [] |
| for line in raw.split("\n"): |
| if line.startswith("X:") and cur: |
| tunes.append("\n".join(cur)); cur = [] |
| cur.append(line) |
| if cur: |
| tunes.append("\n".join(cur)) |
| tunes = [t.strip() for t in tunes if "X:" in t][:5] |
|
|
| for i, t in enumerate(tunes, 1): |
| print(f"\n===== GPT JIG #{i} =====\n{t}") |
| with open("data/generated_gpt.abc", "w", encoding="utf-8") as f: |
| f.write("\n\n".join(tunes) + "\n") |
| print("\n[zapisano -> data/generated_gpt.abc]") |
|
|
