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@ -117,7 +117,14 @@ default_cfgs = {
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_em_ra2-66250f76.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_em_ra2-66250f76.pth',
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input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882),
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input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882),
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'efficientnet_el': _cfg(
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'efficientnet_el': _cfg(
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url='', input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904),
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url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el.pth',
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input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904),
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'efficientnet_es_pruned': _cfg(
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url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_es_pruned75.pth'),
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'efficientnet_el_pruned': _cfg(
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url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el_pruned70.pth',
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input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904),
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'efficientnet_cc_b0_4e': _cfg(url=''),
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'efficientnet_cc_b0_4e': _cfg(url=''),
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'efficientnet_cc_b0_8e': _cfg(url=''),
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'efficientnet_cc_b0_8e': _cfg(url=''),
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@ -1115,6 +1122,12 @@ def efficientnet_es(pretrained=False, **kwargs):
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'efficientnet_es', channel_multiplier=1.0, depth_multiplier=1.0, pretrained=pretrained, **kwargs)
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'efficientnet_es', channel_multiplier=1.0, depth_multiplier=1.0, pretrained=pretrained, **kwargs)
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return model
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return model
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@register_model
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def efficientnet_es_pruned(pretrained=False, **kwargs):
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""" EfficientNet-Edge Small Pruned. For more info: https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0"""
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model = _gen_efficientnet_edge(
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'efficientnet_es_pruned', channel_multiplier=1.0, depth_multiplier=1.0, pretrained=pretrained, **kwargs)
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return model
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@register_model
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@register_model
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def efficientnet_em(pretrained=False, **kwargs):
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def efficientnet_em(pretrained=False, **kwargs):
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@ -1131,6 +1144,12 @@ def efficientnet_el(pretrained=False, **kwargs):
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'efficientnet_el', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs)
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'efficientnet_el', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs)
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return model
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return model
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@register_model
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def efficientnet_el_pruned(pretrained=False, **kwargs):
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""" EfficientNet-Edge-Large pruned. For more info: https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0"""
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model = _gen_efficientnet_edge(
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'efficientnet_el_pruned', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs)
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return model
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@register_model
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@register_model
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def efficientnet_cc_b0_4e(pretrained=False, **kwargs):
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def efficientnet_cc_b0_4e(pretrained=False, **kwargs):
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