class_docstr: Left-to-right Transformer language model.
class_docstr_tok: ["Left-to-right","Transformer","language","model","."]
docstr: Lightning calls this inside the validation loop with the data from the validation dataloader
  passed in as `batch`.
docstr_tok: ["Lightning","calls","this","inside","the","validation","loop","with","the","data","from","the","validation","dataloader","passed","in","as","`","batch","`","."]
code: def validation_step(self, batch, batch_idx):
      """
      Lightning calls this inside the validation loop with the data from the validation dataloader
      passed in as `batch`.
      """
      return self.eval_step(batch, batch_idx)
  
imports: import json
  import math
  from typing import Dict, Optional
  import numpy
  import torch
  import torch.utils.data
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from nemo.collections.common.losses import SmoothedCrossEntropyLoss
  from nemo.collections.common.metrics import GlobalAverageLossMetric
  from nemo.collections.common.parts import transformer_weights_init
  from nemo.collections.nlp.data import SentenceDataset, TarredSentenceDataset
  from nemo.collections.nlp.metrics import SequencePerplexity
  from nemo.collections.nlp.modules.common import TokenClassifier
  from nemo.collections.nlp.modules.common.lm_utils import get_transformer
  from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.modelPT import ModelPT
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 6 for calling the TransformerLMModel obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) and returns: self