From 18bf520ad12297dac4f9992ce497030259ca1aa2 Mon Sep 17 00:00:00 2001 From: Ross Wightman Date: Sat, 22 May 2021 21:55:37 -0700 Subject: [PATCH] Add eca_nfnet_l2/l3 defs for future training --- timm/models/nfnet.py | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/timm/models/nfnet.py b/timm/models/nfnet.py index 3c21eea1..1b67581e 100644 --- a/timm/models/nfnet.py +++ b/timm/models/nfnet.py @@ -110,6 +110,12 @@ default_cfgs = dict( eca_nfnet_l1=_dcfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ecanfnet_l1_ra2-7dce93cd.pth', pool_size=(8, 8), input_size=(3, 256, 256), test_input_size=(3, 320, 320), crop_pct=1.0), + eca_nfnet_l2=_dcfg( + url='', + pool_size=(9, 9), input_size=(3, 288, 288), test_input_size=(3, 352, 352), crop_pct=1.0), + eca_nfnet_l3=_dcfg( + url='', + pool_size=(10, 10), input_size=(3, 320, 320), test_input_size=(3, 384, 384), crop_pct=1.0), nf_regnet_b0=_dcfg( url='', pool_size=(6, 6), input_size=(3, 192, 192), test_input_size=(3, 256, 256), first_conv='stem.conv'), @@ -244,6 +250,12 @@ model_cfgs = dict( eca_nfnet_l1=_nfnet_cfg( depths=(2, 4, 12, 6), feat_mult=2, group_size=64, bottle_ratio=0.25, attn_layer='eca', attn_kwargs=dict(), act_layer='silu'), + eca_nfnet_l2=_nfnet_cfg( + depths=(3, 6, 18, 9), feat_mult=2, group_size=64, bottle_ratio=0.25, + attn_layer='eca', attn_kwargs=dict(), act_layer='silu'), + eca_nfnet_l3=_nfnet_cfg( + depths=(4, 8, 24, 12), feat_mult=2, group_size=64, bottle_ratio=0.25, + attn_layer='eca', attn_kwargs=dict(), act_layer='silu'), # EffNet influenced RegNet defs. # NOTE: These aren't quite the official ver, ch_div=1 must be set for exact ch counts. I round to ch_div=8. @@ -814,6 +826,22 @@ def eca_nfnet_l1(pretrained=False, **kwargs): return _create_normfreenet('eca_nfnet_l1', pretrained=pretrained, **kwargs) +@register_model +def eca_nfnet_l2(pretrained=False, **kwargs): + """ ECA-NFNet-L2 w/ SiLU + My experimental 'light' model w/ F2 repeats, 2.0x final_conv mult, 64 group_size, .25 bottleneck & ECA attn + """ + return _create_normfreenet('eca_nfnet_l2', pretrained=pretrained, **kwargs) + + +@register_model +def eca_nfnet_l3(pretrained=False, **kwargs): + """ ECA-NFNet-L3 w/ SiLU + My experimental 'light' model w/ F3 repeats, 2.0x final_conv mult, 64 group_size, .25 bottleneck & ECA attn + """ + return _create_normfreenet('eca_nfnet_l3', pretrained=pretrained, **kwargs) + + @register_model def nf_regnet_b0(pretrained=False, **kwargs): """ Normalization-Free RegNet-B0