code: def test_transformers_context_expansion(self, results_base_path):
      emb = TransformerWordEmbeddings(
          "distilbert-base-uncased",
          use_context=True,
          use_context_separator=True,
          respect_document_boundaries=True,
      )
  
      # previous and next sentence as context
      sentence_previous = Sentence("How is it?")
      sentence_next = Sentence("Then again, maybe not...")
  
      # test expansion for sentence without context
      sentence = Sentence("This is great!")
      expanded, _ = emb._expand_sentence_with_context(sentence=sentence)
      assert (
          " ".join([token.text for token in expanded])
          == "[FLERT] This is great ! [FLERT]"
      )
  
      # test expansion for with previous and next as context
      sentence = Sentence("This is great.")
      sentence._previous_sentence = sentence_previous
      sentence._next_sentence = sentence_next
      expanded, _ = emb._expand_sentence_with_context(sentence=sentence)
      assert (
          " ".join([token.text for token in expanded])
          == "How is it ? [FLERT] This is great . [FLERT] Then again , maybe not ..."
      )
  
      # test expansion if first sentence is document boundary
      sentence = Sentence("This is great?")
      sentence_previous.is_document_boundary = True
      sentence._previous_sentence = sentence_previous
      sentence._next_sentence = sentence_next
      expanded, _ = emb._expand_sentence_with_context(sentence=sentence)
      assert (
          " ".join([token.text for token in expanded])
          == "[FLERT] This is great ? [FLERT] Then again , maybe not ..."
      )
  
      # test expansion if we don't use context
      emb.context_length = 0
      sentence = Sentence("I am here.")
      sentence._previous_sentence = sentence_previous
      sentence._next_sentence = sentence_next
      expanded, _ = emb._expand_sentence_with_context(sentence=sentence)
      assert (
          " ".join([token.text for token in expanded]) == "I am here ."
      )
  
imports: import importlib.util
  import warnings
  import pytest
  import torch
  from PIL import Image
  from transformers.utils import is_detectron2_available
  from flair.data import BoundingBox, Dictionary, Sentence
  from flair.embeddings import TransformerJitWordEmbeddings, TransformerWordEmbeddings
  from flair.models import SequenceTagger
  from tests.embedding_test_utils import BaseEmbeddingsTest
label_desc: Use image node_id 2 for calling the TestTransformerWordEmbeddings obj's underlying member method code with example usage: obj.test_transformers_context_expansion(results_base_path) without return types