def METHOD_NAME(x, rv):
    x_full = ((x[:, None] * tile_factors[None, :]).view(-1)[:input_length * batch_size * num_labels]
                .view(batch_size, input_length, num_labels))
    rv_full = ((rv[:, None] * tile_factors_rv[None, :]).view(-1)[:input_length * batch_size * num_realval]
                .view(batch_size, input_length, num_realval))
    log_probs = torch.log_softmax(x_full, 2)
    return custom_ctc_f(log_probs, targets, rv_full, targets_realvals, input_lengths, target_lengths, 2.2, 0, blank1, 'mean', True)