code: def forward(self, image):
      features = self.feature_extractor(image)
      z, ljd = self.encode(features)
  
      if self.training:
          return z, ljd
      else:
          return self.anomaly_map_generator(z)
  
file_path: anomalib/src/anomalib/models/uflow/torch_model.py
imports: import torch.nn
  from FrEIA import framework
  from FrEIA import modules
  from anomalib.models.components.flow import AllInOneBlock
  from .anomaly_map import AnomalyMapGenerator
  from .feature_extraction import get_feature_extractor
label_desc: Use image node_id 4 for calling the UflowModel obj's underlying member method code with example usage: obj.forward(image) and returns: z,  ljd, self