(num_classes=1000, pretrained='imagenet')
return model
r"""Densenet-201 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`
r"""Densenet-201 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`
r Densenet - 201 model from Densely Connected Convolutional Networks <https : // arxiv . org / pdf / 1608 . 06993 . pdf >
def densenet201(num_classes=1000, pretrained='imagenet'):
    r"""Densenet-201 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`
    """
    model = models.densenet201(pretrained=False)
    if pretrained is not None:
        settings = pretrained_settings['densenet201'][pretrained]
        model = load_pretrained(model, num_classes, settings)
    model = modify_densenets(model)
    return model
def densenet201 ( num_classes = 1000 , pretrained = 'imagenet' ) : model = models . densenet201 ( pretrained = False ) if pretrained is not None : settings = pretrained_settings [ 'densenet201' ] [ pretrained ] model = load_pretrained ( model , num_classes , settings ) model = modify_densenets ( model ) return model