import pytest
import torch

from timm import list_models, create_model


@pytest.mark.timeout(300)
@pytest.mark.parametrize('model_name', list_models(exclude_filters='*efficientnet_l2*'))
@pytest.mark.parametrize('batch_size', [1])
def test_model_forward(model_name, batch_size):
    """Run a single forward pass with each model"""
    model = create_model(model_name, pretrained=False)
    model.eval()

    inputs = torch.randn((batch_size, *model.default_cfg['input_size']))
    outputs = model(inputs)

    assert outputs.shape[0] == batch_size
    assert not torch.isnan(outputs).any(), 'Output included NaNs'