CountVectorizer does not lowercase() entries in vocabulary when `lowercase` is set to `True`

Describe the bug

The default value of for lowercase in CountVectorizer is True. This has the effect that all content of documents is lowercased by default. However, the entries in the vocabulary are not lowercased. So if the vocabulary contains uppercase characters it won’t match against the content in the documents. I think CountVectorizer should either

1. lowercase the vocabulary as well when lowercase is True or
2. not allow upper case characters in the vocabulary when lowercase is True

Steps/Code to Reproduce

Expected Results

Actual Results

import numpy as np
from sklearn.feature_extraction.text import CountVectorizer

def test_count_vectorizer():
    voc = ["A", "B", "C"]
    documents = ["A B C"]

    count_model = CountVectorizer(
        ngram_range=(1, 1),
        vocabulary=voc,
    )
    x = count_model.fit_transform(documents).toarray()
    assert np.array_equal(x, [[1, 1, 1]])  # x is [[0, 0, 0]]; should be [[1, 1, 1]]

Versions

   setuptools: 51.0.0
      sklearn: 0.23.2
        numpy: 1.19.4
        scipy: 1.5.4
       Cython: 0.29.21
       pandas: 1.1.5
   matplotlib: 3.3.3
       joblib: 1.0.0
threadpoolctl: 2.1.0
Built with OpenMP: True

[zitorelova]

take

[philipp-eisen]

Yeah that’s what I meant with the message before. Sorry for not being very clear.