code: def _allocate_output(self, windows, shape):
          
          if self.dtype == int64_dtype:
              return super(CustomClassifier, self)._allocate_output(
                  windows,
                  shape,
              )
  
          # This is a little bit of a hack.  We might not know what the
          # categories for a LabelArray are until it's actually been loaded, so
          # we need to look at the underlying data.
          return windows[0].data.empty_like(shape)
docs: Override the default array allocation to produce a LabelArray when we
          have a string-like dtype.