Problem tracing binary CNN model after recent tracing optimization
Closed this issue · 8 comments
Prerequisites
Please make sure to check off these prerequisites before submitting a bug report.
- Test that the bug appears on the current version of the master branch. Make sure to include the commit hash of the commit you checked out.
- Check that the issue hasn't already been reported, by checking the currently open issues.
- If there are steps to reproduce the problem, make sure to write them down below.
- If relevant, please include the hls4ml project files, which were created directly before and/or after the bug.
Quick summary
Error when running tracing on a binary cnn (though I do not think the fact that the network is binary is important).
Details
When I tried to run tracing on a binary CNN (from #740):
https://gist.github.com/jmitrevs/0455fde237ccdc778c619e853e64dde6
it causes an error:
Traceback (most recent call last):
File "/Users/jmitrevs/work/hls4ml/test/pytest/profile_binary_cnn.py", line 103, in <module>
test_model2("Vivado", "io_parallel")
File "/Users/jmitrevs/work/hls4ml/test/pytest/profile_binary_cnn.py", line 98, in test_model2
keras_trace = hls4ml.model.profiling.get_ymodel_keras(model2, X)
File "/Users/jmitrevs/work/hls4ml/hls4ml/model/profiling.py", line 592, in get_ymodel_keras
and layer.activation.__name__ != "linear"
AttributeError: 'NoneType' object has no attribute '__name__'. Did you mean: '__ne__'?
The code seems to be new, from #863.
Steps to Reproduce
Run the file in the linked "gist" using the main branch of hls4ml.
I am including @AdrianAlan and @jmduarte because they were involved in the latest tracing updates.
Thanks for catching that. I will take a look.
I am not sure it's a complete fix. When I attempted the fairly straightforward fix of checking that it's not None, I ran into isuses when activation was a string.
We should validate the fix on this, as well.
The fix LGTM.
@jmitrevs What do you mean when you say you ran into issues? When you add, let's say, activation='relu', in L33 in your example, the output looks all right, but the affected layer is out of order. Is that what you refer to?