def ssl_resnext50_32x4d(pretrained=True, **kwargs):
    """Constructs a semi-supervised ResNeXt-50 32x4 model pre-trained on YFCC100M dataset and finetuned on ImageNet
    `"Billion-scale Semi-Supervised Learning for Image Classification" <https://arxiv.org/abs/1905.00546>`_
    Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/
    """
    model_args = dict(block=Bottleneck, layers=[3, 4, 6, 3], cardinality=32, base_width=4, **kwargs)
    return _create_resnet('ssl_resnext50_32x4d', pretrained, **model_args)
Constructs a semi-supervised ResNeXt-50 32x4 model pre-trained on YFCC100M dataset and finetuned on ImageNet
    `"Billion-scale Semi-Supervised Learning for Image Classification" <https://arxiv.org/abs/1905.00546>`_
    Weights from https://github.com/facebookresearch/semi-supervised-ImageNet1K-models/
    
analyze/convnexts4nd/src/models/baselines/resnet_timm.py