Hi @scarecrow21,
Thanks for your reply.
I have in mind, doing something like FbProphet, where I can make a prediction of the next 30 days looking to the whole past.

NCz3fVW.png720×432 73.6 KB

I am trying to do something like this:

def plot_results_multiple(predicted_data, true_data,length):
   plt.plot(scaler.inverse_transform(true_data.reshape(-1, 1))[length:])
   plt.plot(scaler.inverse_transform(np.array(predicted_data).reshape(-1, 1))[length:])
   plt.show()

#predict lenght consecutive values from a real one
def predict_sequences_multiple(model, firstValue,length):
  prediction_seqs = []
  curr_frame = firstValue
 
for i in range(length): 
    predicted = []        
    
    print(predict_with_pytorch(model, curr_frame[newaxis,:,:]))
    predicted.append(predict_with_pytorch(model, curr_frame[newaxis,:,:])[0,0])
    
    curr_frame = curr_frame[0:]
    curr_frame = np.insert(curr_frame[0:], i+1, predicted[-1], axis=0)
    
    prediction_seqs.append(predicted[-1])
    
return prediction_seqs

predict_length=60
predictions = predict_sequences_multiple(model, total_x[-1], predict_length)
print(scaler.inverse_transform(np.array(predictions).reshape(-1, 1)))
plot_results_multiple(predictions, total_y, predict_length)