docstr: Initializes the BERTTextClassifier model.
docstr_tok: ["Initializes","the","BERTTextClassifier","model","."]
code: def __init__(self, cfg: DictConfig, trainer: Trainer = None):
      """Initializes the BERTTextClassifier model."""
      # shared params for dataset and data loaders
      self.dataset_cfg = cfg.dataset
      self.class_weights = None
  
      super().__init__(cfg=cfg, trainer=trainer)
  
      self.classifier = SequenceClassifier(
          hidden_size=self.hidden_size,
          num_classes=cfg.dataset.num_classes,
          num_layers=cfg.classifier_head.num_output_layers,
          activation="relu",
          log_softmax=False,
          dropout=cfg.classifier_head.fc_dropout,
          use_transformer_init=True,
          idx_conditioned_on=0,
      )
  
      self.create_loss_module()
  
      # setup to track metrics
      self.classification_report = ClassificationReport(
          num_classes=cfg.dataset.num_classes,
          mode="micro",
          dist_sync_on_step=True,
      )
  
      # register the file containing the labels into the artifacts to get stored in the '.nemo' file later
      if (
          "class_labels" in cfg
          and "class_labels_file" in cfg.class_labels
          and cfg.class_labels.class_labels_file
      ):
          self.register_artifact(
              "class_labels.class_labels_file",
              cfg.class_labels.class_labels_file,
          )
  
imports: import os
  from typing import Dict, List, Optional
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.losses import CrossEntropyLoss
  from nemo.collections.nlp.data.text_classification import TextClassificationDataset, calc_class_weights
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import SequenceClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.exportable import Exportable
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new TextClassificationModel object from inherited base classes: NLPModel, Exportable with example: obj = TextClassificationModel(cfg, trainer)