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Add maxvit_rmlp_tiny_rw_256 model def and weights w/ 84.2 top-1 @ 256, 84.8 @ 320

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Ross Wightman 2022-09-07 10:27:11 -07:00
parent da6f8f5a40
commit c1b3cea19d
1 changed files with 15 additions and 0 deletions
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15
timm/models/maxxvit.py
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@ -121,6 +121,9 @@ default_cfgs = {
'maxvit_rmlp_nano_rw_256': _cfg( 'maxvit_rmlp_nano_rw_256': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_rmlp_nano_rw_256_sw-c17bb0d6.pth', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_rmlp_nano_rw_256_sw-c17bb0d6.pth',
input_size=(3, 256, 256), pool_size=(8, 8)), input_size=(3, 256, 256), pool_size=(8, 8)),
'maxvit_rmlp_tiny_rw_256': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_rmlp_tiny_rw_256_sw-2da819a5.pth',
input_size=(3, 256, 256), pool_size=(8, 8)),
'maxvit_tiny_pm_256': _cfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)), 'maxvit_tiny_pm_256': _cfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)),
'maxxvit_nano_rw_256': _cfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)), 'maxxvit_nano_rw_256': _cfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)),
@ -515,6 +518,13 @@ model_cfgs = dict(
stem_width=(32, 64), stem_width=(32, 64),
**_rw_max_cfg(rel_pos_type='mlp'), **_rw_max_cfg(rel_pos_type='mlp'),
), ),
maxvit_rmlp_tiny_rw_256=MaxxVitCfg(
embed_dim=(64, 128, 256, 512),
depths=(2, 2, 5, 2),
block_type=('M',) * 4,
stem_width=(32, 64),
**_rw_max_cfg(rel_pos_type='mlp'),
),
maxvit_tiny_pm_256=MaxxVitCfg( maxvit_tiny_pm_256=MaxxVitCfg(
embed_dim=(64, 128, 256, 512), embed_dim=(64, 128, 256, 512),
depths=(2, 2, 5, 2), depths=(2, 2, 5, 2),
@ -1721,6 +1731,11 @@ def maxvit_rmlp_nano_rw_256(pretrained=False, **kwargs):
return _create_maxxvit('maxvit_rmlp_nano_rw_256', pretrained=pretrained, **kwargs) return _create_maxxvit('maxvit_rmlp_nano_rw_256', pretrained=pretrained, **kwargs)
@register_model
def maxvit_rmlp_tiny_rw_256(pretrained=False, **kwargs):
return _create_maxxvit('maxvit_rmlp_tiny_rw_256', pretrained=pretrained, **kwargs)
@register_model @register_model
def maxvit_tiny_pm_256(pretrained=False, **kwargs): def maxvit_tiny_pm_256(pretrained=False, **kwargs):
return _create_maxxvit('maxvit_tiny_pm_256', pretrained=pretrained, **kwargs) return _create_maxxvit('maxvit_tiny_pm_256', pretrained=pretrained, **kwargs)