import pytest

torch = pytest.importorskip("torch")
from torch import nn  # noqa: E402

from mitointeract_recovery.model import MitoInteractHead, TargetScaler  # noqa: E402


def test_head_output_shape():
    model = MitoInteractHead(16, 12, projection_dim=8, hidden_dim=16, dropout=0.0)
    output = model(torch.randn(4, 16), torch.randn(4, 12))
    assert output.shape == (4,)


def test_head_uses_no_batch_norm():
    model = MitoInteractHead(16, 12, projection_dim=8, hidden_dim=16)
    assert not any(
        isinstance(module, nn.modules.batchnorm._BatchNorm)
        for module in model.modules()
    )


def test_target_scaler_round_trip():
    values = torch.tensor([3.0, 5.0, 7.0, 9.0])
    scaler = TargetScaler.fit(values)
    assert torch.allclose(scaler.decode(scaler.encode(values)), values)


def test_mismatched_batches_rejected():
    model = MitoInteractHead(16, 12, projection_dim=8, hidden_dim=16)
    with pytest.raises(ValueError):
        model(torch.randn(3, 16), torch.randn(4, 12))