44f6cac0bbb0d7969ece849cea078c508df7041b,category_encoders/hashing.py,HashingEncoder,transform,#HashingEncoder#Any#Any#,250

Before Change

        Call _transform() if you want to use single CPU with all samples
        
        if X is None or self.cols is None:
            raise AttributeError("None data or feature input")

        self.X = X
        self.data_lines = len(X)
        if self.max_sample == 0 and self.max_process == 1:

After Change

        // then make sure that it is the right size
        if X.shape[1] != self._dim:
            raise ValueError("Unexpected input dimension %d, expected %d" % (X.shape[1], self._dim, ))

        if not self.cols:
            return X

Instances