def __iter__(self):
        """
        For each index document, compute cosine similarity against all other
        documents in the index and yield the result.
        """
        # turn off query normalization (vectors in the index are already normalized, save some CPU)
        norm, self.normalize = self.normalize, False

        for chunk in self.iter_chunks():
            if 1 > chunk.shape[0]:
                for sim in self[chunk]:
                    yield sim
            else:
                yield self[chunk]

        self.normalize = norm # restore normalization
dataset/ETHPy150Open largelymfs/topical_word_embeddings/TWE-1/gensim/similarities/docsim.py/Similarity.__iter__/swapped operands of `>`