I'm testing the RNN model of mxnet. The tutorial here does not work and the error message said many functions had been deprecated. I did not find the up-to-date tutorial for RNN. There are still some examples in the mxnet project. But for RNN, the examples only show how to train a model using training set. They don't show how to use the trained model to make further prediction. The training code is as follows:
model.fit(
train_data = data_train,
eval_data = data_val,
eval_metric = mx.metric.Perplexity(invalid_label),
kvstore = args.kv_store,
optimizer = args.optimizer,
optimizer_params = { 'learning_rate': args.lr,
'momentum': args.mom,
'wd': args.wd },
initializer = mx.init.Xavier(factor_type="in", magnitude=2.34),
num_epoch = args.num_epochs,
batch_end_callback = mx.callback.Speedometer(args.batch_size, args.disp_batches))
Does someone know how to use the trained RNN model to make inference or prediction?
I must clearify that I'm looking for how to use RNN model to make prediction, not CNN or other models.
Thank you very much for helping me!!!