content: #  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  from typing import Tuple
  
  import numpy as np
  from scipy.sparse import csr_matrix
  from sklearn.base import BaseEstimator
  from sklearn.feature_extraction.text import CountVectorizer
  from typing_extensions import Annotated
  
  from zenml import step
  
  
  @step
  def vectorizer(
      train: np.ndarray, test: np.ndarray
  ) -> Tuple[
      Annotated[BaseEstimator, "count_vec"],
      Annotated[csr_matrix, "X_train"],
      Annotated[csr_matrix, "X_test"],
  ]:
      count_vec = CountVectorizer(ngram_range=(1, 4), min_df=3)
      train = count_vec.fit_transform(train)
      test = count_vec.transform(test)
      return count_vec, train, test
  