print('Done !')
### Load dataset
print('Load dataset ... ', end='')
d_train = TextDataset(word2idx, fp_train_labeled, train=True)
d_val = TextDataset(word2idx, fp_train_labeled, train=True, val=True)
train_loader = DataLoader(d_train, batch_size=batch_size, shuffle=True)
val_loader = DataLoader(d_val, batch_size=batch_size, shuffle=False)
### Train model
print('Train LSTM ... ')
model = LSTMClassifier(embedding_dim, hidden_dim, num_layers, batch_size)
model.init_weights()
model.embedding.weight = torch.nn.Parameter(torch.Tensor(word2vec.wv.syn0))
model.embedding.weight.requires_grad = False
model.cuda()
print(model)
criterion = nn.NLLLoss()
optimizer = optim.Adam(
filter(lambda p: p.requires_grad, model.parameters()))
for epoch in range(4):
train(epoch, model, criterion, optimizer, train_loader)
validate(epoch, model, val_loader)
print('Done !')
