relax tolerance on inference test

Author: rwightman

tests/test_models.py

@@ -146,18 +146,18 @@ def test_model_inference(model_name, batch_size):
         rand_output = model(rand_tensors['input'])
         rand_features = model.forward_features(rand_tensors['input'])
         rand_pre_logits = model.forward_head(rand_features, pre_logits=True)
-        assert torch.allclose(rand_output, rand_tensors['output'])
-        assert torch.allclose(rand_features, rand_tensors['features'])
-        assert torch.allclose(rand_pre_logits, rand_tensors['pre_logits'])
+        assert torch.allclose(rand_output, rand_tensors['output'], rtol=1e-3, atol=1e-5)
+        assert torch.allclose(rand_features, rand_tensors['features'], rtol=1e-3, atol=1e-5)
+        assert torch.allclose(rand_pre_logits, rand_tensors['pre_logits'], rtol=1e-3, atol=1e-5)
 
         def _test_owl(owl_input):
             owl_output = model(owl_input)
             owl_features = model.forward_features(owl_input)
             owl_pre_logits = model.forward_head(owl_features.clone(), pre_logits=True)
             assert owl_output.softmax(1).argmax(1) == 24  # owl
-            assert torch.allclose(owl_output, owl_tensors['output'])
-            assert torch.allclose(owl_features, owl_tensors['features'])
-            assert torch.allclose(owl_pre_logits, owl_tensors['pre_logits'])
+            assert torch.allclose(owl_output, owl_tensors['output'], rtol=1e-3, atol=1e-5)
+            assert torch.allclose(owl_features, owl_tensors['features'], rtol=1e-3, atol=1e-5)
+            assert torch.allclose(owl_pre_logits, owl_tensors['pre_logits'], rtol=1e-3, atol=1e-5)
 
         _test_owl(owl_tensors['input'])  # test with original pp owl tensor
         _test_owl(pp(test_owl).unsqueeze(0))  # re-process from original jpg