code: def interpret_output(self, batch_output):
      if self.is_training:
          return True
      else:
          infer_type = look_up_operations(
              self.autoencoder_param.inference_type, SUPPORTED_INFERENCE
          )
          if infer_type == "encode":
              return self.output_decoder.decode_batch(
                  {"window_embedded": batch_output["embedded"]},
                  batch_output["location"][:, 0:1],
              )
          if infer_type == "encode-decode":
              return self.output_decoder.decode_batch(
                  {
                      "window_generated_image": batch_output[
                          "generated_image"
                      ]
                  },
                  batch_output["location"][:, 0:1],
              )
          if infer_type == "sample":
              return self.output_decoder.decode_batch(
                  {"generated_image": batch_output["generated_image"]},
                  None,
              )
          if infer_type == "linear_interpolation":
              return self.output_decoder.decode_batch(
                  {"generated_image": batch_output["generated_image"]},
                  batch_output["location"][:, :2],
              )
  
imports: import tensorflow
  from niftynet.application.base_application import BaseApplication
  from niftynet.engine.application_factory import ApplicationNetFactory
  from niftynet.engine.application_factory import OptimiserFactory
  from niftynet.engine.application_variables import CONSOLE
  from niftynet.engine.application_variables import NETWORK_OUTPUT
  from niftynet.engine.application_variables import TF_SUMMARIES
  from niftynet.engine.sampler_linear_interpolate_v2 import LinearInterpolateSampler
  from niftynet.contrib.csv_reader.sampler_linear_interpolate_v2_csv import LinearInterpolateSamplerCSV
  from niftynet.engine.sampler_resize_v2 import ResizeSampler
  from niftynet.contrib.csv_reader.sampler_resize_v2_csv import ResizeSamplerCSV
  from niftynet.contrib.csv_reader.csv_reader import CSVReader
  from niftynet.engine.windows_aggregator_identity import WindowAsImageAggregator
  from niftynet.io.image_reader import ImageReader
  from niftynet.layer.loss_autoencoder import LossFunction
  from niftynet.utilities.util_common import look_up_operations
label_desc: Use image node_id 6 for calling the AutoencoderApplication obj's underlying member method code with example usage: obj.interpret_output(batch_output) and returns: True, self, self, self, self