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@ -3,6 +3,9 @@
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Paper: `Characterizing signal propagation to close the performance gap in unnormalized ResNets`
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- https://arxiv.org/abs/2101.08692
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NOTE: These models are a work in progress, no pretrained weights yet but I'm currently training some.
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Details may change, especially once the paper authors release their official models.
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Hacked together by / copyright Ross Wightman, 2021.
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"""
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import math
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@ -34,11 +37,11 @@ def _dcfg(url='', **kwargs):
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# FIXME finish
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default_cfgs = {
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'nf_regnet_b0': _dcfg(url=''),
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'nf_regnet_b1': _dcfg(url='', input_size=(3, 240, 240)),
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'nf_regnet_b2': _dcfg(url='', input_size=(3, 256, 256)),
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'nf_regnet_b3': _dcfg(url='', input_size=(3, 272, 272)),
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'nf_regnet_b4': _dcfg(url='', input_size=(3, 320, 320)),
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'nf_regnet_b5': _dcfg(url='', input_size=(3, 384, 384)),
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'nf_regnet_b1': _dcfg(url='', input_size=(3, 240, 240), pool_size=(8, 8)),
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'nf_regnet_b2': _dcfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)),
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'nf_regnet_b3': _dcfg(url='', input_size=(3, 272, 272), pool_size=(9, 9)),
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'nf_regnet_b4': _dcfg(url='', input_size=(3, 320, 320), pool_size=(10, 10)),
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'nf_regnet_b5': _dcfg(url='', input_size=(3, 384, 384), pool_size=(12, 12)),
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'nf_resnet26': _dcfg(url='', first_conv='stem.conv'),
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'nf_resnet50': _dcfg(url='', first_conv='stem.conv'),
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