34', 'resnet50',
             'resnet101', 'resnet152', 'resnext50_32x4d', 'resnext101_32x8d', 'wide_resnet50_2', 'wide_resnet101_2'
        weights (WeightsEnum, optional): The pretrained weights for the model
        norm_layer (callable): it is recommended to use the default value. For details visit:
            (https://github.com/facebookresearch/maskrcnn-benchmark/issues/267)
        trainable_layers (int): number of trainable (not frozen) layers starting from final block.
            Valid values are between 0 and 5, with 5 meaning all backbone layers are trainable.
        returned_layers (list of int): The layers of the network to return. Each entry must be in ``[1, 4]``.
            By default, all layers are returned.
        extra_blocks (ExtraFPNBlock or None): if provided, extra operations will
            be performed. It is expected to take the fpn features, the original
            features and the names of the original features as input, and returns
            a new list of feature maps and their corresponding names. By
            default, a ``LastLevelMaxPool`` is used.
    ©