def METHOD_NAME(self):
    head = AssociativeEmbeddingHead(
        in_channels=32,
        num_keypoints=17,
        tag_dim=1,
        tag_per_keypoint=True,
        deconv_out_channels=None)
    feats = [torch.rand(1, 32, 64, 64)]
    output = head.forward(feats)  # should be (heatmaps, tags)
    self.assertTrue(is_tuple_of(output, torch.Tensor))
    self.assertEqual(output[0].shape, (1, 17, 64, 64))
    self.assertEqual(output[1].shape, (1, 17, 64, 64))