class_docstr: Dataset for inference pipeline.
  
  Args:
      sents: list of strings
      example_builder: instance of BertExampleBuilder
class_docstr_tok: ["Dataset","for","inference","pipeline",".","Args",":","sents",":","list","of","strings","example_builder",":","instance","of","BertExampleBuilder"]
code: def __init__(
      self, sents: List[str], example_builder: BertExampleBuilder
  ) -> None:
      self.examples = []
      for source in sents:
          example = example_builder.build_bert_example(
              source, infer=True
          )
          if example is None:
              raise ValueError("Cannot build example from: " + source)
          self.examples.append(example)
  
file_path: NeMo/nemo/collections/nlp/data/text_normalization_as_tagging/thutmose_tagger_dataset.py
imports: from typing import Dict, List, Optional
  import numpy
  from nemo.collections.nlp.data.text_normalization_as_tagging.bert_example import BertExampleBuilder, read_input_file
  from nemo.core.classes.dataset import Dataset
  from nemo.core.neural_types import ChannelType, IntType, LabelsType, MaskType, NeuralType
label_desc: Use image node_id 2 to create a new ThutmoseTaggerTestDataset object from inherited base classes: Dataset with example: obj = ThutmoseTaggerTestDataset(sents, example_builder)