class_docstr: SifVectorizer tests.
class_docstr_tok: ["SifVectorizer","tests","."]
docstr: Check that vectorizer correctly processes out of vocabulary words.
docstr_tok: ["Check","that","vectorizer","correctly","processes","out","of","vocabulary","words","."]
code: def test_oov(self, keyed_vectors):
      """Check that vectorizer correctly processes out of vocabulary words."""
      sif = SifVectorizer(keyed_vectors, npc=0).fit(tokenized_sentences)
      matrix = sif.transform([["out", "of"], ["vocab", "words"]])
      expected = np.zeros_like(matrix)
      np.testing.assert_array_equal(matrix, expected)
  
file_path: textvec/tests/test_vectorizers.py
imports: import math
  import pytest
  from scipy.spatial.distance import cosine
  from scipy.sparse.linalg import norm
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import Pipeline
  from sklearn.dummy import DummyClassifier
  from textvec.vectorizers import *
label_desc: Use image node_id 5 for calling the TestSif obj's underlying member method code with example usage: obj.test_oov(keyed_vectors) without return types