RuntimeWarning during the model conversion. The converted coreml model gave wrong output. about coremltools HOT 3 CLOSED

Loading untrusted PyTorch tensors is a security risk. So I'm not going to try and reproduce your results.

Have you tried specifying compute_precision=ct.precision.FLOAT32 in your ct.convert call? Your code is not setting that. So your Core ML model is most likely using float16 while your PyTorch model is most likely using float32. This would explain why you're getting overflow in your Core ML model but not your PyTorch model.

from coremltools.

@TobyRoseman
Thank you so much for your help.
It works with the setting compute_precision=ct.precision.FLOAT32

Best,
Xiaohui

from coremltools.

Thanks for letting us know. I'm going to close this issue.

from coremltools.