class_docstr: Supervised vectorizers tests.
class_docstr_tok: ["Supervised","vectorizers","tests","."]
docstr: Check that vectorizer correctly processes count matrix with
  out of vocabulary words.
docstr_tok: ["Check","that","vectorizer","correctly","processes","count","matrix","with","out","of","vocabulary","words","."]
code: def test_oov(self, count_matrix_dataset, vectorizer):
      """Check that vectorizer correctly processes count matrix with
      out of vocabulary words.
      """
      cv, x, y = count_matrix_dataset
      v = vectorizer()
      v.fit(x, y)
      sentences = ["out of", "vocab words"]
      transformed = cv.transform(sentences)
      matrix = v.transform(transformed).toarray()
      np.testing.assert_allclose(matrix, np.zeros_like(matrix))
  
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 3 for calling the TestVectorizers obj's underlying member method code with example usage: obj.test_oov(count_matrix_dataset, vectorizer) without return types