docstr: Processes the training examples in the given training data in-place.
docstr_tok: ["Processes","the","training","examples","in","the","given","training","data","in-place","."]
code: def process_training_data(
      self, training_data: TrainingData
  ) -> TrainingData:
      """Processes the training examples in the given training data in-place."""
      self.process(training_data.training_examples)
      return training_data
  
imports: import numpy
  import logging
  from bpemb import BPEmb
  from typing import Any, Text, Dict, List, Type
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
  from rasa.nlu.tokenizers.tokenizer import Tokenizer
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import DENSE_FEATURIZABLE_ATTRIBUTES, FEATURIZER_CLASS_ALIAS
  from rasa.shared.nlu.constants import TEXT, TEXT_TOKENS, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
label_desc: Use image node_id 7 for calling the BytePairFeaturizer obj's underlying member method code with example usage: obj.process_training_data(training_data) and returns: training_data