code: def get_psanet(
      num_classes=1, backbone="resnet50", pretrained=True, **kwargs
  ):
      r"""PS Attention Network
  
      Parameters
      ----------
      num_classes : int
          Number of classes
      pretrained : bool, default True
          This will load pretrained backbone network, that was trained on ImageNet.
      """
  
      model = PSANet(
          num_classes=num_classes,
          backbone=backbone,
          pretrained=pretrained,
          **kwargs,
      )
      return model
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.basic import _ConvBNReLU
  from pywick.models.segmentation.da_basenets.segbase import SegBaseModel
  from pywick.models.segmentation.da_basenets.fcn import _FCNHead
label_desc: Use image node_id 1 for calling a global function with example usage: get_psanet(num_classes, backbone, pretrained) and returns: model