def METHOD_NAME(weights, torch_layer, hidden_size):
    # set torch weights for 1-to-1 comparison
    np_query_key = np.asarray(weights[0])
    np_value = np.asarray(weights[1])
    np_dense = np.asarray(weights[2])
    set_param(
        torch_layer.self_attention.query_key,
        torch.tensor(np_query_key).transpose(1, 2).contiguous().view(-1, hidden_size),
    )
    set_param(
        torch_layer.self_attention.value,
        torch.tensor(np_value).transpose(1, 2).contiguous().view(-1, hidden_size),
    )
    set_param(
        torch_layer.output.dense,
        torch.tensor(np_dense).view(-1, hidden_size).contiguous().transpose(0, 1),
    )