def METHOD_NAME(self):
    for dtype in TEST_DTYPES:
        batch_size = 32
        embeddings = torch.randn(batch_size, 64).type(dtype).to(TEST_DEVICE)
        labels = torch.arange(batch_size)
        for miner in [
            self.dist_miner,
            self.normalized_dist_miner,
            self.normalized_dist_miner_squared,
            self.sim_miner,
        ]:
            a1, p, _, _ = miner(embeddings, labels)
            self.assertTrue(len(a1) == 0)
            self.assertTrue(len(p) == 0)