def METHOD_NAME(self):
    codec = dict(
        type='MSRAHeatmap',
        input_size=(192, 256),
        heatmap_size=(48, 64),
        sigma=2)
    head = VisPredictHead(
        pose_cfg=dict(
            type='HeatmapHead',
            in_channels=32,
            out_channels=17,
            deconv_out_channels=None,
            loss=dict(type='KeypointMSELoss', use_target_weight=True),
            decoder=codec))
    feats = [torch.rand(1, 32, 128, 128)]
    output_pose, output_vis = head.forward(feats)
    self.assertIsInstance(output_pose, torch.Tensor)
    self.assertEqual(output_pose.shape, (1, 17, 128, 128))
    self.assertIsInstance(output_vis, torch.Tensor)
    self.assertEqual(output_vis.shape, (1, 17))