def METHOD_NAME(batch_size, raw_outputs):
    output_per_box = []
    fq_weights = []
    for i in range(batch_size):
        box_outs = OrderedDict()
        for layer_node, data in raw_outputs[0].items():
            if layer_node in fq_weights:
                continue
            if layer_node.get_node().friendly_name.endswith('fq_weights_1'):
                fq_weights.append(layer_node)
                box_outs[layer_node] = data
            elif data.ndim == 0:
                box_outs[layer_node] = np.array([data])
            elif data.shape[0] <= i:
                box_outs[layer_node] = data
            else:
                box_outs[layer_node] = np.expand_dims(data[i], axis=0)
        output_per_box.append(box_outs)
    return output_per_box