class_docstr: SifVectorizer tests.
class_docstr_tok: ["SifVectorizer","tests","."]
docstr: Check that vocab size of trained SifVectorizer is equal
  to number of unique words in input data.
docstr_tok: ["Check","that","vocab","size","of","trained","SifVectorizer","is","equal","to","number","of","unique","words","in","input","data","."]
code: def test_vocab(self, keyed_vectors):
      """Check that vocab size of trained SifVectorizer is equal
      to number of unique words in input data."""
      sif = SifVectorizer(keyed_vectors).fit(tokenized_sentences)
      assert len(sif.vocab) == 6
  
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 4 for calling the TestSif obj's underlying member method code with example usage: obj.test_vocab(keyed_vectors) without return types