class composer.models.DeepLabV3Hparams(initializers=<factory>, num_classes=None, backbone_arch='resnet101', backbone_weights=None, use_plus=True, sync_bn=True, ignore_index=-1, cross_entropy_weight=1.0, dice_weight=0.0)[source]#
YAHP interface for


  • num_classes (int) โ€“ Number of classes in the segmentation task.

  • backbone_arch (str, optional) โ€“ The architecture to use for the backbone. Must be either ['resnet50', 'resnet101']. Default: 'resnet101'.

  • backbone_weights (str, optional) โ€“ If specified, the PyTorch pre-trained weights to load for the backbone. Currently, only [โ€˜IMAGENET1K_V1โ€™, โ€˜IMAGENET1K_V2โ€™] are supported. Default: None.

  • use_plus (bool, optional) โ€“ If True, use DeepLabv3+ head instead of DeepLabv3. Default: True.

  • sync_bn (bool, optional) โ€“ If True, replace all BatchNorm layers with SyncBatchNorm layers. Default: True.

  • initializers (List[Initializer], optional) โ€“ Initializers for the model. [] for no initialization. Default: [].