code: def test_all_tag_proba_embedding(
      self, example_sentence, loaded_pretrained_model
  ):
      loaded_pretrained_model.predict(
          example_sentence, return_probabilities_for_all_classes=True
      )
      for token in example_sentence:
          assert len(
              token.get_tags_proba_dist(
                  loaded_pretrained_model.label_type
              )
          ) == len(loaded_pretrained_model.label_dictionary)
          score_sum = 0.0
          for label in token.get_tags_proba_dist(
              loaded_pretrained_model.label_type
          ):
              assert label.data_point == token
              score_sum += label.score
          assert abs(score_sum - 1.0) < 1.0e-5
  
file_path: flair/tests/models/test_sequence_tagger.py
imports: import pytest
  import flair
  from flair.embeddings import FlairEmbeddings, WordEmbeddings
  from flair.models import SequenceTagger
  from flair.trainers import ModelTrainer
  from tests.model_test_utils import BaseModelTest
label_desc: Use image node_id 5 for calling the TestSequenceTagger obj's underlying member method code with example usage: obj.test_all_tag_proba_embedding(example_sentence, loaded_pretrained_model) without return types