def densenet121(pretrained=False, **kwargs):
    r"""Densenet-121 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_

    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
    """
    model = DenseNet(num_init_features=64, growth_rate=32, block_config=(6, 12, 24, 16),
                     **kwargs)
    if pretrained:
        _load_state_dict(model, model_urls['densenet121'])
    return model
def densenet121(pretrained=False, **kwargs):
    r"""Densenet-121 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_

    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
    """
    model = DenseNet(num_init_features=64, growth_rate=32, block_config=(6, 12, 24, 16),
                     **kwargs)
    if pretrained:
        _load_state_dict(model, model_urls['densenet121'])
    return model
def densenet121 ( pretrained = False , * * kwargs ) : model = DenseNet ( num_init_features = 64 , growth_rate = 32 , block_config = ( 6 , 12 , 24 , 16 ) , * * kwargs ) if pretrained : _load_state_dict ( model , model_urls [ 'densenet121' ] ) return model
r"""Densenet-121 model from
    `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_

    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
r Densenet - 121 model from Densely Connected Convolutional Networks <https : // arxiv . org / pdf / 1608 . 06993 . pdf > _