class_docstr: Model for end-to-end speech intent classification and slot filling, which is formulated as a speech-to-sequence task
class_docstr_tok: ["Model","for","end-to-end","speech","intent","classification","and","slot","filling",",","which","is","formulated","as","a","speech-to-sequence","task"]
code: def validation_step(self, batch, batch_idx, dataloader_idx=0):
      metrics = self.validation_pass(batch, batch_idx, dataloader_idx)
      if (
          type(self.trainer.val_dataloaders) == list
          and len(self.trainer.val_dataloaders) > 1
      ):
          self.validation_step_outputs[dataloader_idx].append(metrics)
      else:
          self.validation_step_outputs.append(metrics)
      return metrics
  
imports: import json
  import os
  import tempfile
  from math import ceil
  from typing import Dict, List, Optional, Union
  import torch
  from omegaconf import DictConfig, OmegaConf, open_dict
  from tqdm.auto import tqdm
  from nemo.collections.asr.data import audio_to_text_dataset
  from nemo.collections.asr.data.audio_to_text_dali import DALIOutputs
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.models.asr_model import ASRModel, ExportableEncDecModel
  from nemo.collections.asr.parts.mixins import ASRBPEMixin, ASRModuleMixin
  from nemo.collections.asr.parts.preprocessing.perturb import process_augmentations
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCBPEDecoding, CTCBPEDecodingConfig
  from nemo.collections.asr.parts.utils.slu_utils import SequenceGenerator, SequenceGeneratorConfig, get_seq_mask
  from nemo.collections.common.losses import SmoothedNLLLoss
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types import AudioSignal, LabelsType, LengthsType, LogprobsType, NeuralType, SpectrogramType
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 9 for calling the SLUIntentSlotBPEModel obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx, dataloader_idx) and returns: metrics