2020-05-07 00:20:58 -04:00
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import pytest
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import torch
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from timm import list_models, create_model
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2020-05-07 10:15:49 -07:00
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@pytest.mark.timeout(300)
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2020-05-07 00:20:58 -04:00
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@pytest.mark.parametrize('model_name', list_models())
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@pytest.mark.parametrize('batch_size', [1])
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def test_model_forward(model_name, batch_size):
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"""Run a single forward pass with each model"""
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model = create_model(model_name, pretrained=False)
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model.eval()
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inputs = torch.randn((batch_size, *model.default_cfg['input_size']))
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outputs = model(inputs)
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assert outputs.shape[0] == batch_size
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assert not torch.isnan(outputs).any(), 'Output included NaNs'
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