class_docstr: Provides common code for text vectorizers (tokenization logic).
class_docstr_tok: ["Provides","common","code","for","text","vectorizers","(","tokenization","logic",")","."]
docstr: Build or fetch the effective stop words list.
  
  Returns
  -------
  stop_words: list or None
          A list of stop words.
docstr_tok: ["Build","or","fetch","the","effective","stop","words","list",".","Returns","--","--","--","-","stop_words",":","list","or","None","A","list","of","stop","words","."]
code: def _get_stop_words(self):
      """
      Build or fetch the effective stop words list.
  
      Returns
      -------
      stop_words: list or None
              A list of stop words.
      """
      if self.stop_words == "english":
          return list(ENGLISH_STOP_WORDS)
      elif isinstance(self.stop_words, str):
          raise ValueError(
              "not a built-in stop list: %s" % self.stop_words
          )
      elif self.stop_words is None:
          return None
      else:  # assume it's a collection
          return list(self.stop_words)
  
imports: from cuml.internals.safe_imports import cpu_only_import
  import cuml.internals.logger
  from cudf.utils.dtypes import min_signed_type
  from cuml.internals.type_utils import CUPY_SPARSE_DTYPES
  import numbers
  from cuml.internals.safe_imports import gpu_only_import
  from functools import partial
  from cuml.common.sparsefuncs import create_csr_matrix_from_count_df
  from cuml.common.sparsefuncs import csr_row_normalize_l1, csr_row_normalize_l2
  from cuml.feature_extraction._stop_words import ENGLISH_STOP_WORDS
  from cuml.common.exceptions import NotFittedError
  from cuml.internals.safe_imports import gpu_only_import_from
label_desc: Use image node_id 3 for calling the _VectorizerMixin obj's underlying member method code with example usage: obj._get_stop_words() and returns: list, None, list