Hi

I've managed to setup and compile your project.

The script main.py runs without errors [see bottom for script output].

However, I can't figure out how to save a trained model and then use it.

I.e. let's say I have an input text file with one line

"Wasted so much money on previous laptops - why did I not buy this from the start.... Extremely happy with this product!"

How do I train the model, i.e. using the 14semeval_laptop dataset, and then use the model on my input text file?

Encase you need to send me something, my email is [email protected]

This is what I get when I run the main.py:
$ python3 main.py -n_epoch 1
[dynet] random seed: 1314159
[dynet] allocating memory: 4096MB
[dynet] memory allocation done.
N opinion: 3041
N dataset: 3041
N opinion: 800
N dataset: 800
Use the saved word embeddings
Embeddings shape: (5302, 300)
Use case-insensitive word embeddings
Parameters: Namespace(attention_type='bilinear', dim_asp=100, dim_opi=30, dim_w=300, dropout=0.5, dropout_asp=0.5, dropout_opi=0.5, ds_name='14semeval_rest', dynet_seed=1314159, flag='glove_840B', model_name='full', n_asp_tags=3, n_epoch=1, n_opi_tags=2, n_steps=5, optimizer='sgd', random_seed=1234, rnn_type='LSTM', running_mode='train-test', sgd_lr=0.07, win=3)
Use pretrained word embeddings
In Epoch 1 / 1:
The dy.parameter(...) call is now DEPRECATED.
There is no longer need to explicitly add parameters to the computation graph.
Any used parameter will be added automatically.
train loss: 18462.82, train precision: 67.54, train recall: 59.55, train f1: 63.29
Current results: precision: 81.03, recall: 77.60, f1: 79.27
$