code: def test_tagged_corpus_statistics():
      train_sentence = Sentence(
          "I love Berlin.", use_tokenizer=True
      ).add_label("label", "class_1")
  
      dev_sentence = Sentence(
          "The sun is shining.", use_tokenizer=True
      ).add_label("label", "class_2")
  
      test_sentence = Sentence(
          "Berlin is sunny.", use_tokenizer=True
      ).add_label("label", "class_1")
  
      class_to_count_dict = Corpus._count_sentence_labels(
          [train_sentence, dev_sentence, test_sentence]
      )
  
      assert "class_1" in class_to_count_dict
      assert "class_2" in class_to_count_dict
      assert class_to_count_dict["class_1"] == 2
      assert class_to_count_dict["class_2"] == 1
  
      tokens_in_sentences = Corpus._get_tokens_per_sentence(
          [train_sentence, dev_sentence, test_sentence]
      )
  
      assert len(tokens_in_sentences) == 3
      assert tokens_in_sentences[0] == 4
      assert tokens_in_sentences[1] == 5
      assert tokens_in_sentences[2] == 4
  
imports: import os
  import pytest
  import flair
  from flair.data import Corpus, Dictionary, Label, Sentence
  from flair.datasets import ColumnCorpus, FlairDatapointDataset, SentenceDataset
label_desc: Use image node_id 12 for calling a global function with example usage: test_tagged_corpus_statistics() without return types