def build_simple_cnn_text_classifier(
    tok2vec: Model, exclusive_classes: bool, nO: Optional[int] = None
) -> Model[List[Doc], Floats2d]:
    """
    Build a simple CNN text classifier, given a token-to-vector model as inputs.
    If exclusive_classes=True, a softmax non-linearity is applied, so that the
    outputs sum to 1. If exclusive_classes=False, a logistic non-linearity
    is applied instead, so that outputs are in the range [0, 1].
    """
    return build_reduce_text_classifier(
        tok2vec=tok2vec,
        exclusive_classes=exclusive_classes,
        use_reduce_first=False,
        use_reduce_last=False,
        use_reduce_max=False,
        use_reduce_mean=True,
        nO=nO,
    )

    Build a simple CNN text classifier, given a token-to-vector model as inputs.
    If exclusive_classes=True, a softmax non-linearity is applied, so that the
    outputs sum to 1. If exclusive_classes=False, a logistic non-linearity
    is applied instead, so that outputs are in the range [0, 1].
    
spacy/ml/models/textcat.py