def METHOD_NAME(self):
    for dtype in TEST_DTYPES:
        angles = [0, 20, 40, 60, 80, 100]
        embeddings = torch.tensor(
            [angle_to_coord(a, normalized=True) for a in angles], dtype=dtype
        ).to(TEST_DEVICE)
        a1, p, a2, n = self.normalized_dist_miner(embeddings, self.labels)
        pos_pairs = torch.stack([a1, p], dim=1)
        neg_pairs = torch.stack([a2, n], dim=1)
        self.helper(pos_pairs, neg_pairs)