def METHOD_NAME(self):
    """Tests trident roi head predict."""
    if not torch.cuda.is_available():
        # RoI pooling only support in GPU
        return unittest.skip('test requires GPU and torch+cuda')
    roi_head = MODELS.build(self.roi_head_cfg)
    roi_head = roi_head.cuda()
    s = 256
    feats = []
    for i in range(len(roi_head.bbox_roi_extractor.featmap_strides)):
        feats.append(
            torch.rand(1, 256, s // (2**(i + 2)),
                       s // (2**(i + 2))).to(device='cuda'))
    image_shapes = [(3, s, s)]
    batch_data_samples = demo_mm_inputs(
        batch_size=1,
        image_shapes=image_shapes,
        num_items=[0],
        num_classes=4,
        with_mask=True,
        device='cuda')['data_samples']
    proposals_list = demo_mm_proposals(
        image_shapes=image_shapes, num_proposals=100, device='cuda')
    roi_head.predict(feats, proposals_list, batch_data_samples)