Using the TFLearn Model

Use the trained model to predict or evaluate:

score = model.evaluate(X_test, Y_test)
print('Test accuracy:', score[0])

The complete code for the TFLearn MNIST classification example is provided in the notebook ch-02_TF_High_Level_Libraries. The output from the TFLearn MNIST example is as follows:

Training Step: 5499  | total loss: 0.42119 | time: 1.817s
| Adam | epoch: 010 | loss: 0.42119 - acc: 0.8860 -- iter: 54900/55000
Training Step: 5500  | total loss: 0.40881 | time: 1.820s
| Adam | epoch: 010 | loss: 0.40881 - acc: 0.8854 -- iter: 55000/55000
--
Test accuracy: 0.9029

You can get more information about TFLearn from the following link: http://tflearn.org/.