1

######Prediction###############


lstm.eval()
train_predict = lstm(dataX.to(device))
data_predict = train_predict.cpu().data.numpy()
dataY_plot = dataY.data.numpy()

## Inverse Normalize 
data_predict = scaler.inverse_transform(data_predict)
dataY_plot = scaler.inverse_transform(dataY_plot)

## Add dates
df_predict = pd.DataFrame(data_predict)
df_predict = df_predict.set_index([dates_list[:-29]])
df_labels = pd.DataFrame(dataY_plot)
df_labels = df_labels.set_index([dates_list[:-29]])