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3 | 3 | Paper: `Characterizing signal propagation to close the performance gap in unnormalized ResNets` |
4 | 4 | - https://arxiv.org/abs/2101.08692 |
5 | 5 |
|
| 6 | +NOTE: These models are a work in progress, no pretrained weights yet but I'm currently training some. |
| 7 | +Details may change, especially once the paper authors release their official models. |
| 8 | +
|
6 | 9 | Hacked together by / copyright Ross Wightman, 2021. |
7 | 10 | """ |
8 | 11 | import math |
@@ -34,11 +37,11 @@ def _dcfg(url='', **kwargs): |
34 | 37 | # FIXME finish |
35 | 38 | default_cfgs = { |
36 | 39 | 'nf_regnet_b0': _dcfg(url=''), |
37 | | - 'nf_regnet_b1': _dcfg(url='', input_size=(3, 240, 240)), |
38 | | - 'nf_regnet_b2': _dcfg(url='', input_size=(3, 256, 256)), |
39 | | - 'nf_regnet_b3': _dcfg(url='', input_size=(3, 272, 272)), |
40 | | - 'nf_regnet_b4': _dcfg(url='', input_size=(3, 320, 320)), |
41 | | - 'nf_regnet_b5': _dcfg(url='', input_size=(3, 384, 384)), |
| 40 | + 'nf_regnet_b1': _dcfg(url='', input_size=(3, 240, 240), pool_size=(8, 8)), |
| 41 | + 'nf_regnet_b2': _dcfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)), |
| 42 | + 'nf_regnet_b3': _dcfg(url='', input_size=(3, 272, 272), pool_size=(9, 9)), |
| 43 | + 'nf_regnet_b4': _dcfg(url='', input_size=(3, 320, 320), pool_size=(10, 10)), |
| 44 | + 'nf_regnet_b5': _dcfg(url='', input_size=(3, 384, 384), pool_size=(12, 12)), |
42 | 45 |
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43 | 46 | 'nf_resnet26': _dcfg(url='', first_conv='stem.conv'), |
44 | 47 | 'nf_resnet50': _dcfg(url='', first_conv='stem.conv'), |
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