class_docstr: APIs to help create and train a BERT-based text classifier.
class_docstr_tok: ["APIs","to","help","create","and","train","a","BERT-based","text","classifier","."]
docstr: Loads a BertClassifierPreprocessor and runs it on the data.
  
  Args:
    train_data: Training data.
    validation_data: Validation data.
  
  Returns:
    Preprocessed training data and preprocessed validation data.
code: def _load_and_run_preprocessor(
      self,
      train_data: text_ds.Dataset,
      validation_data: text_ds.Dataset,
  ) -> Tuple[text_ds.Dataset, text_ds.Dataset]:
      """Loads a BertClassifierPreprocessor and runs it on the data.
  
      Args:
        train_data: Training data.
        validation_data: Validation data.
  
      Returns:
        Preprocessed training data and preprocessed validation data.
      """
      self._text_preprocessor = preprocessor.BertClassifierPreprocessor(
          seq_len=self._model_options.seq_len,
          do_lower_case=self._model_spec.do_lower_case,
          uri=self._model_spec.get_path(),
          model_name=self._model_spec.name,
          tokenizer=self._hparams.tokenizer,
      )
      return (
          self._text_preprocessor.preprocess(train_data),
          self._text_preprocessor.preprocess(validation_data),
      )
  
imports: import abc
  import os
  import tempfile
  from typing import Any, Optional, Sequence, Tuple
  import tensorflow
  from tensorflow_addons import optimizers
  import tensorflow_hub
  from mediapipe.model_maker.python.core.data import dataset
  from mediapipe.model_maker.python.core.tasks import classifier
  from mediapipe.model_maker.python.core.utils import hub_loader
  from mediapipe.model_maker.python.core.utils import loss_functions
  from mediapipe.model_maker.python.core.utils import metrics
  from mediapipe.model_maker.python.core.utils import model_util
  from mediapipe.model_maker.python.core.utils import quantization
  from mediapipe.model_maker.python.text.text_classifier import bert_tokenizer
  from mediapipe.model_maker.python.text.text_classifier import dataset
  from mediapipe.model_maker.python.text.text_classifier import hyperparameters
  from mediapipe.model_maker.python.text.text_classifier import model_options
  from mediapipe.model_maker.python.text.text_classifier import model_spec
  from mediapipe.model_maker.python.text.text_classifier import model_with_tokenizer
  from mediapipe.model_maker.python.text.text_classifier import preprocessor
  from mediapipe.model_maker.python.text.text_classifier import text_classifier_options
  from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer
  from mediapipe.tasks.python.metadata.metadata_writers import text_classifier
label_desc: Use image node_id 4 for calling the _BertClassifier obj's underlying member method code with example usage: obj._load_and_run_preprocessor(train_data, validation_data) and returns: self,  self