An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
With models from https://github.com/Res2Net/Res2Net-PretrainedModels
prune with FPGMPruner
I got same error as :
File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/speedup/compressor.py", line 518, in speedup_model
fix_mask_conflict(self.masks, self.bound_model, self.dummy_input)
File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/utils/mask_conflict.py", line 54, in fix_mask_conflict
masks = fix_channel_mask.fix_mask()
File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/utils/mask_conflict.py", line 264, in fix_mask
assert len(set(num_channels_list)) == 1
With models from https://github.com/Res2Net/Res2Net-PretrainedModels prune with FPGMPruner I got same error as : File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/speedup/compressor.py", line 518, in speedup_model fix_mask_conflict(self.masks, self.bound_model, self.dummy_input) File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/utils/mask_conflict.py", line 54, in fix_mask_conflict masks = fix_channel_mask.fix_mask() File "/usr/local/lib/python3.7/dist-packages/nni/compression/pytorch/utils/mask_conflict.py", line 264, in fix_mask assert len(set(num_channels_list)) == 1
How could I get rid of such problems?