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Rename test_tiny* -> test*. Fix ByobNet BasicBlock attn location and add test_byobnet model.

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This commit is contained in:
Ross Wightman 2024-07-09 11:53:11 -07:00
parent 66a0eb4673
commit 55101028bb
3 changed files with 23 additions and 20 deletions
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27
timm/models/byobnet.py
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@ -261,8 +261,9 @@ class BasicBlock(nn.Module):
def forward(self, x): def forward(self, x):
shortcut = x shortcut = x
x = self.conv1_kxk(x) x = self.conv1_kxk(x)
x = self.conv2_kxk(x)
x = self.attn(x) x = self.attn(x)
x = self.conv2_kxk(x)
x = self.attn_last(x)
x = self.drop_path(x) x = self.drop_path(x)
if self.shortcut is not None: if self.shortcut is not None:
x = x + self.shortcut(shortcut) x = x + self.shortcut(shortcut)
@ -439,7 +440,6 @@ class EdgeBlock(nn.Module):
downsample, in_chs, out_chs, downsample, in_chs, out_chs,
stride=stride, dilation=dilation, apply_act=False, layers=layers, stride=stride, dilation=dilation, apply_act=False, layers=layers,
) )
self.conv1_kxk = layers.conv_norm_act( self.conv1_kxk = layers.conv_norm_act(
in_chs, mid_chs, kernel_size, in_chs, mid_chs, kernel_size,
stride=stride, dilation=dilation[0], groups=groups, drop_layer=drop_block, stride=stride, dilation=dilation[0], groups=groups, drop_layer=drop_block,
@ -1835,16 +1835,19 @@ model_cfgs = dict(
stem_chs=64, stem_chs=64,
), ),
test_tiny_resnet=ByoModelCfg( test_byobnet=ByoModelCfg(
blocks=( blocks=(
ByoBlockCfg(type='basic', d=1, c=24, s=1, gs=1, br=0.25), ByoBlockCfg(type='edge', d=1, c=32, s=2, gs=0, br=0.5),
ByoBlockCfg(type='basic', d=1, c=32, s=2, gs=1, br=0.25), ByoBlockCfg(type='dark', d=1, c=64, s=2, gs=0, br=0.5),
ByoBlockCfg(type='basic', d=1, c=64, s=2, gs=1, br=0.25), ByoBlockCfg(type='basic', d=1, c=128, s=2, gs=32, br=0.25),
ByoBlockCfg(type='basic', d=1, c=128, s=2, gs=1, br=0.25), ByoBlockCfg(type='bottle', d=1, c=256, s=2, gs=64, br=0.25),
), ),
stem_chs=32, stem_chs=24,
stem_pool='maxpool', downsample='avg',
stem_pool='',
act_layer='relu', act_layer='relu',
attn_layer='se',
attn_kwargs=dict(rd_ratio=0.25),
), ),
) )
@ -2048,7 +2051,7 @@ default_cfgs = generate_default_cfgs({
first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'), first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
), ),
'test_tiny_byobnet.untrained': _cfgr( 'test_byobnet.untrained': _cfgr(
# hf_hub_id='timm/', # hf_hub_id='timm/',
input_size=(3, 160, 160), crop_pct=0.875, pool_size=(5, 5), input_size=(3, 160, 160), crop_pct=0.875, pool_size=(5, 5),
), ),
@ -2357,7 +2360,7 @@ def mobileone_s4(pretrained=False, **kwargs) -> ByobNet:
@register_model @register_model
def test_tiny_byobnet(pretrained=False, **kwargs) -> ByobNet: def test_byobnet(pretrained=False, **kwargs) -> ByobNet:
""" Minimal test ResNet (BYOB based) model. """ Minimal test ResNet (BYOB based) model.
""" """
return _create_byobnet('test_tiny_byobnet', pretrained=pretrained, **kwargs) return _create_byobnet('test_byobnet', pretrained=pretrained, **kwargs)

6
timm/models/efficientnet.py
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@ -1610,7 +1610,7 @@ default_cfgs = generate_default_cfgs({
url='https://github.com/huawei-noah/CV-Backbones/releases/download/v1.2.0/tinynet_e.pth', url='https://github.com/huawei-noah/CV-Backbones/releases/download/v1.2.0/tinynet_e.pth',
hf_hub_id='timm/'), hf_hub_id='timm/'),
"test_tiny_efficientnet.untrained": _cfg( "test_efficientnet.untrained": _cfg(
# hf_hub_id='timm/' # hf_hub_id='timm/'
input_size=(3, 160, 160), pool_size=(5, 5)), input_size=(3, 160, 160), pool_size=(5, 5)),
}) })
@ -2540,8 +2540,8 @@ def tinynet_e(pretrained=False, **kwargs) -> EfficientNet:
@register_model @register_model
def test_tiny_efficientnet(pretrained=False, **kwargs) -> EfficientNet: def test_efficientnet(pretrained=False, **kwargs) -> EfficientNet:
model = _gen_test_efficientnet('test_tiny_efficientnet', pretrained=pretrained, **kwargs) model = _gen_test_efficientnet('test_efficientnet', pretrained=pretrained, **kwargs)
return model return model

10
timm/models/vision_transformer.py
View File

@ -1937,7 +1937,7 @@ default_cfgs = {
'vit_so150m_patch16_reg4_map_256.untrained': _cfg( 'vit_so150m_patch16_reg4_map_256.untrained': _cfg(
input_size=(3, 256, 256)), input_size=(3, 256, 256)),
'test_tiny_vit.untrained': _cfg( 'test_vit.untrained': _cfg(
input_size=(3, 160, 160), crop_pct=0.875), input_size=(3, 160, 160), crop_pct=0.875),
} }
@ -3110,11 +3110,11 @@ def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visio
@register_model @register_model
def test_tiny_vit(pretrained: bool = False, **kwargs) -> VisionTransformer: def test_vit(pretrained: bool = False, **kwargs) -> VisionTransformer:
""" ViT-TestTiny """ ViT Test
""" """
model_args = dict(patch_size=16, embed_dim=64, depth=4, num_heads=1, mlp_ratio=3) model_args = dict(patch_size=16, embed_dim=64, depth=6, num_heads=2, mlp_ratio=3)
model = _create_vision_transformer('test_tiny_vit', pretrained=pretrained, **dict(model_args, **kwargs)) model = _create_vision_transformer('test_vit', pretrained=pretrained, **dict(model_args, **kwargs))
return model return model