| import torch | |
| from nanochat.gpt import GPT, GPTConfig | |
| def test_tiny_model_forward(): | |
| # Use a tiny n_embd that would have triggered the bug (n_embd < 32) | |
| config = GPTConfig( | |
| n_head=2, | |
| n_kv_head=2, | |
| n_embd=16, | |
| vocab_size=128, | |
| sequence_len=32 | |
| ) | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| print(f"Using device: {device}") | |
| model = GPT(config).to(device) | |
| model.init_weights() | |
| # Create dummy input | |
| idx = torch.randint(0, config.vocab_size, (1, 8), device=device) | |
| print("Running forward pass...") | |
| try: | |
| logits = model(idx) | |
| print("Forward pass successful!") | |
| assert logits.shape == (1, 8, config.vocab_size) | |
| except Exception as e: | |
| print(f"Forward pass failed with error: {e}") | |
| raise e | |
| if __name__ == "__main__": | |
| test_tiny_model_forward() | |