Add MobileNetV3 RA4 (mnv4 recipe) weights
parent
b3f3a005a0
commit
ebbe530ee4
timm/models
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@ -916,6 +916,10 @@ default_cfgs = generate_default_cfgs({
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interpolation='bicubic',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_large_100_ra-f55367f5.pth',
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hf_hub_id='timm/'),
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'mobilenetv3_large_100.ra4_e3600_r224_in1k': _cfg(
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hf_hub_id='timm/',
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interpolation='bicubic', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD,
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crop_pct=0.95, test_input_size=(3, 256, 256), test_crop_pct=1.0),
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'mobilenetv3_large_100.miil_in21k_ft_in1k': _cfg(
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interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.),
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origin_url='https://github.com/Alibaba-MIIL/ImageNet21K',
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@ -928,9 +932,10 @@ default_cfgs = generate_default_cfgs({
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origin_url='https://github.com/Alibaba-MIIL/ImageNet21K',
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paper_ids='arXiv:2104.10972v4',
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interpolation='bilinear', mean=(0., 0., 0.), std=(1., 1., 1.), num_classes=11221),
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'mobilenetv3_large_150d.untrained': _cfg(
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#hf_hub_id='timm/',
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),
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'mobilenetv3_large_150d.ra4_e3600_r256_in1k': _cfg(
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hf_hub_id='timm/',
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mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD,
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input_size=(3, 256, 256), crop_pct=0.95, pool_size=(8, 8), test_input_size=(3, 320, 320), test_crop_pct=1.0),
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'mobilenetv3_small_050.lamb_in1k': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_small_050_lambc-4b7bbe87.pth',
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