Basic forward pass test for all registered models

tests/test_inference.py

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+import pytest
+import torch
+
+from timm import list_models, create_model
+
+
+@pytest.mark.timeout(60)
+@pytest.mark.parametrize('model_name', list_models())
+@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'