How to use the srsly.cloudpickle.dump function in srsly

trainer.each_epoch.append(report_progress)
        trainer.nb_epoch = nb_epoch
        trainer.dropout = 0.3
        trainer.batch_size = 128
        trainer.dropout_decay = 0.0
        train_X = model.ops.asarray(train_X, dtype="float32")
        y_onehot = to_categorical(train_y)
        for X, y in trainer.iterate(train_X, y_onehot):
            yh, backprop = model.begin_update(X, drop=trainer.dropout)
            loss = ((yh - y) ** 2.0).sum() / y.shape[0]
            backprop(yh - y, optimizer)
            epoch_loss[-1] += loss
        with model.use_params(optimizer.averages):
            print("Avg dev.: %.3f" % model.evaluate(dev_X, dev_y))
            with open("out.pickle", "wb") as file_:
                pickle.dump(model, file_, -1)