mirrors/pytorch-image-models
1
0
Fork 0
mirror of https://github.com/huggingface/pytorch-image-models.git synced 2025-06-03 15:01:08 +08:00
Code Issues Projects Releases Wiki Activity

Reduce tolerance on model inference 'owl' test, pillow output varies a lot, was failing locally

Browse Source
This commit is contained in:
Ross Wightman 2024-11-26 10:55:52 -08:00 committed by Ross Wightman
parent 1ab02a11a1
commit 0903d98162
1 changed files with 8 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
tests/test_models.py
View File

@ -146,21 +146,21 @@ 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'], rtol=1e-3, atol=1e-4)
assert torch.allclose(rand_features, rand_tensors['features'], rtol=1e-3, atol=1e-4)
assert torch.allclose(rand_pre_logits, rand_tensors['pre_logits'], rtol=1e-3, atol=1e-4)
assert torch.allclose(rand_output, rand_tensors['output'], rtol=1e-3, atol=1e-4), 'rand output does not match'
assert torch.allclose(rand_features, rand_tensors['features'], rtol=1e-3, atol=1e-4), 'rand features do not match'
assert torch.allclose(rand_pre_logits, rand_tensors['pre_logits'], rtol=1e-3, atol=1e-4), 'rand pre_logits do not match'
def _test_owl(owl_input):
def _test_owl(owl_input, tol=(1e-3, 1e-4)):
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'], rtol=1e-3, atol=1e-4)
assert torch.allclose(owl_features, owl_tensors['features'], rtol=1e-3, atol=1e-4)
assert torch.allclose(owl_pre_logits, owl_tensors['pre_logits'], rtol=1e-3, atol=1e-4)
assert torch.allclose(owl_output, owl_tensors['output'], rtol=tol[0], atol=tol[1]), 'owl output does not match'
assert torch.allclose(owl_features, owl_tensors['features'], rtol=tol[0], atol=tol[1]), 'owl output does not match'
assert torch.allclose(owl_pre_logits, owl_tensors['pre_logits'], rtol=tol[0], atol=tol[1]), 'owl output does not match'
_test_owl(owl_tensors['input']) # test with original pp owl tensor
_test_owl(pp(test_owl).unsqueeze(0)) # re-process from original jpg
_test_owl(pp(test_owl).unsqueeze(0), tol=(1e-1, 1e-1)) # re-process from original jpg, Pillow output can change a lot btw ver
@pytest.mark.base