PyTorch Implementation of PyramidNet

Usage

$ python main.py --block_type basic --depth 110 --alpha 84 --outdir results

Model	Test Error (median of 3 runs)	Test Error (in paper)	Training Time
PyramidNet-110 (alpha=84)	4.40	4.26 ± 0.23	11h40m
PyramidNet-110 (alpha=270)	3.92 (1 run)	3.73 ± 0.04	24h12m*
PyramidNet-164 bottleneck (alpha=270)		3.48 ± 0.20
PyramidNet-272 bottleneck (alpha=200)		3.31 ± 0.08

Han, Dongyoon, Jiwhan Kim, and Junmo Kim. "Deep pyramidal residual networks." The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 5927-5935. arXiv:1610.02915, Torch implementation, Caffe implementation, PyTorch implementation

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