from __future__ import annotations

import tempfile
import unittest
from pathlib import Path

try:
    import torch
except ImportError:  # pragma: no cover
    torch = None


@unittest.skipUnless(torch is not None, "PyTorch is not installed")
class WarmStartTest(unittest.TestCase):
    def test_weights_only_warm_start_is_strict_and_described(self) -> None:
        from scripts.train import _warm_start_model
        from turn_detection.models.tiny_tcn import TinyTCNConfig, TinyTurnDetector

        config = TinyTCNConfig(
            channels=16,
            num_blocks=1,
            kernel_size=3,
            dilation_cycle=(1,),
            attention_channels=8,
            head_hidden=8,
            dropout=0.0,
        )
        torch.manual_seed(1)
        source = TinyTurnDetector(config)
        torch.manual_seed(2)
        target = TinyTurnDetector(config)
        with tempfile.TemporaryDirectory() as directory:
            path = Path(directory) / "best.pt"
            torch.save(
                {
                    "model_config": source.model_config(),
                    "model_state": source.state_dict(),
                    "epoch": 3,
                    "metadata": {"run_name": "source"},
                },
                path,
            )
            evidence = _warm_start_model(target, path, torch)

        for expected, actual in zip(source.parameters(), target.parameters(), strict=True):
            torch.testing.assert_close(actual, expected)
        self.assertEqual(evidence["mode"], "weights_only_fresh_optimizer")
        self.assertEqual(evidence["selected_epoch"], 3)
        self.assertEqual(evidence["source_run"], "source")
        self.assertEqual(len(evidence["sha256"]), 64)


if __name__ == "__main__":
    unittest.main()