class_docstr: Supervised vectorizers tests.
class_docstr_tok: ["Supervised","vectorizers","tests","."]
docstr: Check that vectorizer accepts parameters from GridSearchCV.
docstr_tok: ["Check","that","vectorizer","accepts","parameters","from","GridSearchCV","."]
code: def test_gridsearchcv(self, count_matrix_dataset, vectorizer):
      """Check that vectorizer accepts parameters from GridSearchCV."""
      cv, x, y = count_matrix_dataset
      pipeline = Pipeline(
          [
              ("vect", vectorizer()),
              ("clf", DummyClassifier()),
          ]
      )
      parameters = {
          "vect__sublinear_tf": (False, True),
      }
      GridSearchCV(pipeline, parameters, cv=2).fit(x, y)
  
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 TestVectorizers obj's underlying member method code with example usage: obj.test_gridsearchcv(count_matrix_dataset, vectorizer) without return types