code: def test_feature_fingerprints_take_into_account_full_array():
      """Tests that fingerprint isn't using summary/abbreviated array info."""
      big_array = np.random.random((128, 128))
  
      f1 = Features(
          big_array, FEATURE_TYPE_SENTENCE, TEXT, "RegexFeaturizer"
      )
      big_array_with_zero = np.copy(big_array)
      big_array_with_zero[64, 64] = 0.0
      f2 = Features(
          big_array_with_zero,
          FEATURE_TYPE_SENTENCE,
          TEXT,
          "RegexFeaturizer",
      )
  
      assert f1.fingerprint() != f2.fingerprint()
  
      f1_sparse = Features(
          scipy.sparse.coo_matrix(big_array),
          FEATURE_TYPE_SENTENCE,
          TEXT,
          "RegexFeaturizer",
      )
  
      f2_sparse = Features(
          scipy.sparse.coo_matrix(big_array_with_zero),
          FEATURE_TYPE_SENTENCE,
          TEXT,
          "RegexFeaturizer",
      )
  
      assert f1_sparse.fingerprint() != f2_sparse.fingerprint()
  
imports: import itertools
  from typing import Optional, Text, List, Dict, Tuple, Any
  import numpy
  import pytest
  import scipy.sparse
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.constants import FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE, TEXT, INTENT
label_desc: Use image node_id 7 for calling a global function with example usage: test_feature_fingerprints_take_into_account_full_array() without return types