(self, dataset_blob)
Restore the pretrained model and classifier.

    Args:
      dataset_blob: The object containts `save_path` used for restoring.
Restore the pretrained model and classifier.
Restore the pretrained model and classifier .
def restore(self, dataset_blob):
    """Restore the pretrained model and classifier.

    Args:
      dataset_blob: The object containts `save_path` used for restoring.
    """
    this_config_is_wavegan = self.this_config_is_wavegan
    m_helper = self.m_helper
    m_classifier_helper = self.m_classifier_helper

    if this_config_is_wavegan:
      m_helper.restore()
      # We don't need restore the `m_classifier_helper` again since `m_helper`
      # and `m_classifier_helper` are two identicial objects.
    else:
      m_helper.restore_best('vae_saver', dataset_blob.save_path,
                            'vae_best_%s.ckpt')
      m_classifier_helper.restore_best(
          'classifier_saver', dataset_blob.save_path, 'classifier_best_%s.ckpt')
def restore ( self , dataset_blob ) : this_config_is_wavegan = self . this_config_is_wavegan m_helper = self . m_helper m_classifier_helper = self . m_classifier_helper if this_config_is_wavegan : m_helper . restore ( ) # We don't need restore the `m_classifier_helper` again since `m_helper` # and `m_classifier_helper` are two identicial objects. else : m_helper . restore_best ( 'vae_saver' , dataset_blob . save_path , 'vae_best_%s.ckpt' ) m_classifier_helper . restore_best ( 'classifier_saver' , dataset_blob . save_path , 'classifier_best_%s.ckpt' )