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@ -48,6 +48,10 @@ default_cfgs = dict(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/convnext_tiny_hnf_a2h-ab7e9df2.pth',
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crop_pct=0.95),
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convnext_tiny_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_tiny_22k_1k_224.pth'),
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convnext_small_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_small_22k_1k_224.pth'),
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convnext_base_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_224.pth'),
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convnext_large_in22ft1k=_cfg(
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@ -55,6 +59,12 @@ default_cfgs = dict(
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convnext_xlarge_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_xlarge_22k_1k_224_ema.pth'),
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convnext_tiny_384_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_tiny_22k_1k_384.pth',
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input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
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convnext_small_384_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_small_22k_1k_384.pth',
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input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
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convnext_base_384_in22ft1k=_cfg(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_384.pth',
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input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
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@ -65,6 +75,10 @@ default_cfgs = dict(
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url='https://dl.fbaipublicfiles.com/convnext/convnext_xlarge_22k_1k_384_ema.pth',
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input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
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convnext_tiny_in22k=_cfg(
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url="https://dl.fbaipublicfiles.com/convnext/convnext_tiny_22k_224.pth", num_classes=21841),
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convnext_small_in22k=_cfg(
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url="https://dl.fbaipublicfiles.com/convnext/convnext_small_22k_224.pth", num_classes=21841),
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convnext_base_in22k=_cfg(
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url="https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_224.pth", num_classes=21841),
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convnext_large_in22k=_cfg(
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@ -405,6 +419,20 @@ def convnext_large(pretrained=False, **kwargs):
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return model
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@register_model
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def convnext_tiny_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_tiny_in22ft1k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_small_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_small_in22ft1k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_base_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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@ -426,6 +454,20 @@ def convnext_xlarge_in22ft1k(pretrained=False, **kwargs):
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return model
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@register_model
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def convnext_tiny_384_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_tiny_384_in22ft1k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_small_384_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_small_384_in22ft1k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_base_384_in22ft1k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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@ -447,6 +489,20 @@ def convnext_xlarge_384_in22ft1k(pretrained=False, **kwargs):
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return model
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@register_model
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def convnext_tiny_in22k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_tiny_in22k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_small_in22k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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model = _create_convnext('convnext_small_in22k', pretrained=pretrained, **model_args)
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return model
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@register_model
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def convnext_base_in22k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs)
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@ -466,6 +522,3 @@ def convnext_xlarge_in22k(pretrained=False, **kwargs):
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model_args = dict(depths=[3, 3, 27, 3], dims=[256, 512, 1024, 2048], **kwargs)
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model = _create_convnext('convnext_xlarge_in22k', pretrained=pretrained, **model_args)
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return model
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