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Change models with mean 0,0,0 std 1,1,1 from int to float for consistency as mentioned in #1355

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Ross Wightman 2022-07-21 17:36:15 -07:00
parent 909705e7ff
commit 1b278136c3
5 changed files with 8 additions and 8 deletions
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4
timm/models/mlp_mixer.py
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@ -85,11 +85,11 @@ default_cfgs = dict(
# Mixer ImageNet-21K-P pretraining
mixer_b16_224_miil_in21k=_cfg(
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil_in21k.pth',
mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', num_classes=11221,
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', num_classes=11221,
),
mixer_b16_224_miil=_cfg(
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil.pth',
mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear',
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear',
),
gmixer_12_224=_cfg(mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD),

4
timm/models/mobilenetv3.py
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@ -41,10 +41,10 @@ default_cfgs = {
interpolation='bicubic',
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_large_100_ra-f55367f5.pth'),
'mobilenetv3_large_100_miil': _cfg(
interpolation='bilinear', mean=(0, 0, 0), std=(1, 1, 1),
interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.),
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mobilenetv3_large_100_1k_miil_78_0.pth'),
'mobilenetv3_large_100_miil_in21k': _cfg(
interpolation='bilinear', mean=(0, 0, 0), std=(1, 1, 1),
interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.),
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mobilenetv3_large_100_in21k_miil.pth', num_classes=11221),
'mobilenetv3_small_050': _cfg(

2
timm/models/mobilevit.py
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@ -34,7 +34,7 @@ def _cfg(url='', **kwargs):
return {
'url': url, 'num_classes': 1000, 'input_size': (3, 256, 256), 'pool_size': (8, 8),
'crop_pct': 0.9, 'interpolation': 'bicubic',
'mean': (0, 0, 0), 'std': (1, 1, 1),
'mean': (0., 0., 0.), 'std': (1., 1., 1.),
'first_conv': 'stem.conv', 'classifier': 'head.fc',
'fixed_input_size': False,
**kwargs

2
timm/models/tresnet.py
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@ -21,7 +21,7 @@ def _cfg(url='', **kwargs):
return {
'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
'crop_pct': 0.875, 'interpolation': 'bilinear',
'mean': (0, 0, 0), 'std': (1, 1, 1),
'mean': (0., 0., 0.), 'std': (1., 1., 1.),
'first_conv': 'body.conv1.0', 'classifier': 'head.fc',
**kwargs
}

4
timm/models/vision_transformer.py
View File

@ -163,12 +163,12 @@ default_cfgs = {
# ViT ImageNet-21K-P pretraining by MILL
'vit_base_patch16_224_miil_in21k': _cfg(
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/vit_base_patch16_224_in21k_miil.pth',
mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', num_classes=11221,
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear', num_classes=11221,
),
'vit_base_patch16_224_miil': _cfg(
url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm'
'/vit_base_patch16_224_1k_miil_84_4.pth',
mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear',
mean=(0., 0., 0.), std=(1., 1., 1.), crop_pct=0.875, interpolation='bilinear',
),
'vit_base_patch16_rpn_224': _cfg(