def METHOD_NAME(self, batched_inputs):
    assert not self.training
    _, _, results, image_sizes = self._forward_once_(batched_inputs, None)
    processed_results = []
    for r, input, image_size in zip(results, batched_inputs, image_sizes):
        height = input.get('height', image_size[0])
        width = input.get('width', image_size[1])
        r = detector_postprocess(r, height, width)
        processed_results.append({'instances': r})
    return processed_results