@supports_config_loading
 def __init__(
 self,
 encoder_name: str = "resnet34",
 encoder_depth: int = 5,
 encoder_weights: Optional[str] = "imagenet",
 decoder_segmentation_channels: int = 256,
 in_channels: int = 3,
 classes: int = 1,
 activation: Optional[Union[str, Callable]] = None,
 upsampling: int = 4,
 aux_params: Optional[dict] = None,
 **kwargs: dict[str, Any],
 ):
 super().__init__()
 self.encoder = get_encoder(
 encoder_name,
 in_channels=in_channels,
 depth=encoder_depth,
 weights=encoder_weights,
 **kwargs,
 )
 self.decoder = SegformerDecoder(
 encoder_channels=self.encoder.out_channels,
 encoder_depth=encoder_depth,
 segmentation_channels=decoder_segmentation_channels,
 )
 self.segmentation_head = SegmentationHead(
 in_channels=decoder_segmentation_channels,
 out_channels=classes,
 activation=activation,
 kernel_size=1,
 upsampling=upsampling,
 )
 if aux_params is not None:
 self.classification_head = ClassificationHead(
 in_channels=self.encoder.out_channels[-1], **aux_params
 )
 else:
 self.classification_head = None
 self.name = "segformer-{}".format(encoder_name)
 self.initialize()