code: def export_model(
      self,
      model_path,
      mask_path=None,
      folder_name=".",
      speedup=False,
      dummy_input=None,
      *args,
      **kwargs,
  ):
      model = self.model
      os.makedirs(folder_name, exist_ok=True)
      model_path = os.path.join(folder_name, model_path)
      if mask_path is not None:
          mask_path = os.path.join(folder_name, mask_path)
      if self._compression_framework == "torch":
          if self._compression_type == "pruning":
              self._nni_compressor.export_model(model_path, mask_path)
              if speedup and not self._applied_speedup:
                  if dummy_input is None:
                      logger.warning(
                          'Missing required parameter "dummy_input" for speed-up, '
                          + "saving compressed model without speed-up."
                      )
                  else:
                      try:
                          model = self.apply_speedup(
                              dummy_input, mask_path
                          )
                      except ValueError:
                          logger.warning(
                              "Error encountered when applying speed-up, "
                              + "saving compressed model without speed-up."
                          )
          torch.save(model.state_dict(), model_path)
      elif self._compression_framework == "tensorflow":
          self.model.save(model_path)
  
file_path: auptimizer/src/aup/compression/Compressor.py
imports: import copy
  import logging
  import os
  from ..utils import check_missing_key
label_desc: Use image node_id 9 for calling the Compressor obj's underlying member method code with example usage: obj.export_model(model_path, mask_path, folder_name, speedup, dummy_input) without return types