code: def initialize_active_learner(active_learner, y_train):
      indices_initial = random_initialization_balanced(y_train)
      y_initial = np.array([y_train[i] for i in indices_initial])
  
      active_learner.initialize_data(indices_initial, y_initial)
  
      return indices_initial
  
file_path: small-text/examples/examplecode/transformers_multiclass_classification.py
imports: import numpy
  from transformers import AutoTokenizer
  from small_text import EmptyPoolException, PoolBasedActiveLearner, PoolExhaustedException, RandomSampling, TransformerBasedClassificationFactory, TransformerModelArguments, random_initialization_balanced
  from examplecode.data.corpus_twenty_news import get_twenty_newsgroups_corpus
  from examplecode.data.example_data_transformers import preprocess_data
  from examplecode.shared import evaluate
label_desc: Use image node_id 3 for calling a global function with example usage: initialize_active_learner(active_learner, y_train) and returns: indices_initial