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@ -873,8 +873,8 @@ def swsl_resnext101_32x16d(pretrained=True, **kwargs):
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@register_model
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def seresnext26d_32x4d(pretrained=False, num_classes=1000, in_chans=3, **kwargs):
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"""Constructs a ResNet-26 v1d model.
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This is technically a 28 layer ResNet, sticking with 'd' modifier from Gluon for now.
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"""Constructs a SE-ResNeXt-26-D model.
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This is technically a 28 layer ResNet, sticking with 'D' modifier from Gluon / bag-of-tricks.
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"""
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default_cfg = default_cfgs['seresnext26d_32x4d']
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model = ResNet(
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@ -889,7 +889,9 @@ def seresnext26d_32x4d(pretrained=False, num_classes=1000, in_chans=3, **kwargs)
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@register_model
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def seresnext26t_32x4d(pretrained=False, num_classes=1000, in_chans=3, **kwargs):
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"""Constructs a ResNet-26 v1d model.
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"""Constructs a SE-ResNet-26-T model.
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This is technically a 28 layer ResNet, like a 'D' bag-of-tricks model but with tiered 24, 48, 64 channels
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in the deep stem. Stem channel counts suggested by Jeremy Howard.
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"""
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default_cfg = default_cfgs['seresnext26t_32x4d']
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model = ResNet(
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