Evaluation mode missing on validation and predict

[ljtruong]

This section in predict()

da-rnn/main.py

Lines 178 to 181 in 8585806

	y_history = numpy_to_tvar(y_history)
	_, input_encoded = t_net.encoder(numpy_to_tvar(X))
	y_pred[y_slc] = t_net.decoder(input_encoded, y_history).cpu().data.numpy()

should be changed to

with torch.no_grad():
  y_history = numpy_to_tvar(y_history)
  _, input_encoded = t_net.encoder(numpy_to_tvar(X))
  y_pred[y_slc] = t_net.decoder(input_encoded, y_history).cpu().data.numpy()

This is required to disable any gradient calculation during validation / prediction in training loop. From my understanding if not included, it wll update weights on each validation / prediction iteration.

This is original final_prediction output

This is with grad turned off during validation / prediction.