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Add maxvit_tiny_rw_224 weights 83.5 @ 224 and maxvit_rmlp_pico_rw_256 relpos weights, 80.5 @ 256, 81.3 @ 320

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Ross Wightman 2022-09-06 16:14:41 -07:00
parent f489f02ad1
commit dc90816f26
1 changed files with 22 additions and 4 deletions
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26
timm/models/maxxvit.py
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@ -110,8 +110,14 @@ default_cfgs = {
'maxvit_nano_rw_256': _cfg( 'maxvit_nano_rw_256': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_nano_rw_256_sw-fb127241.pth', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_nano_rw_256_sw-fb127241.pth',
input_size=(3, 256, 256), pool_size=(8, 8)), input_size=(3, 256, 256), pool_size=(8, 8)),
'maxvit_tiny_rw_224': _cfg(url=''), 'maxvit_tiny_rw_224': _cfg(
'maxvit_tiny_rw_256': _cfg(url='', input_size=(3, 256, 256), pool_size=(8, 8)), url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_tiny_rw_224_sw-7d0dffeb.pth'),
'maxvit_tiny_rw_256': _cfg(
url='',
input_size=(3, 256, 256), pool_size=(8, 8)),
'maxvit_rmlp_pico_rw_256': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights-maxx/maxvit_rmlp_pico_rw_256_sw-8d82f2c6.pth',
input_size=(3, 256, 256), pool_size=(8, 8)),
'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)),
@ -139,7 +145,7 @@ class MaxxVitTransformerCfg:
pool_type: str = 'avg2' pool_type: str = 'avg2'
rel_pos_type: str = 'bias' rel_pos_type: str = 'bias'
rel_pos_dim: int = 512 # for relative position types w/ MLP rel_pos_dim: int = 512 # for relative position types w/ MLP
partition_stride: int = 32 partition_ratio: int = 32
window_size: Optional[Tuple[int, int]] = None window_size: Optional[Tuple[int, int]] = None
grid_size: Optional[Tuple[int, int]] = None grid_size: Optional[Tuple[int, int]] = None
init_values: Optional[float] = None init_values: Optional[float] = None
@ -495,6 +501,13 @@ model_cfgs = dict(
stem_width=(32, 64), stem_width=(32, 64),
**_rw_max_cfg(), **_rw_max_cfg(),
), ),
maxvit_rmlp_pico_rw_256=MaxxVitCfg(
embed_dim=(32, 64, 128, 256),
depths=(2, 2, 5, 2),
block_type=('M',) * 4,
stem_width=(24, 32),
**_rw_max_cfg(rel_pos_type='mlp'),
),
maxvit_rmlp_nano_rw_256=MaxxVitCfg( maxvit_rmlp_nano_rw_256=MaxxVitCfg(
embed_dim=(64, 128, 256, 512), embed_dim=(64, 128, 256, 512),
depths=(1, 2, 3, 1), depths=(1, 2, 3, 1),
@ -1458,7 +1471,7 @@ def cfg_window_size(cfg: MaxxVitTransformerCfg, img_size: Tuple[int, int]):
if cfg.window_size is not None: if cfg.window_size is not None:
assert cfg.grid_size assert cfg.grid_size
return cfg return cfg
partition_size = img_size[0] // cfg.partition_stride, img_size[1] // cfg.partition_stride partition_size = img_size[0] // cfg.partition_ratio, img_size[1] // cfg.partition_ratio
cfg = replace(cfg, window_size=partition_size, grid_size=partition_size) cfg = replace(cfg, window_size=partition_size, grid_size=partition_size)
return cfg return cfg
@ -1698,6 +1711,11 @@ def maxvit_tiny_rw_256(pretrained=False, **kwargs):
return _create_maxxvit('maxvit_tiny_rw_256', pretrained=pretrained, **kwargs) return _create_maxxvit('maxvit_tiny_rw_256', pretrained=pretrained, **kwargs)
@register_model
def maxvit_rmlp_pico_rw_256(pretrained=False, **kwargs):
return _create_maxxvit('maxvit_rmlp_pico_rw_256', pretrained=pretrained, **kwargs)
@register_model @register_model
def maxvit_rmlp_nano_rw_256(pretrained=False, **kwargs): 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)