Output of classifier.predict Tensorflow extract probabiltity When I do a prediction with my DNN clasifier I get a dictionary like this. 

{'probabilities': array([9.9912649e-01, 8.7345875e-04, 8.5633601e-12], dtype=float32), 'logits': array([ 12.641698,   5.599522, -12.840958], dtype=float32), 'classes': array(['0'], dtype=object), 'class_ids': array([0])}


Can someone explain me the values of probability and logits? Why the three values ? 

The docs just states 


  Evaluated values of predictions tensors.


And do not refer (the docs) to a struct/explanation of the output 

Thanks!
At the probabilities key you will find the probabilities of every label. Tensorflow just chooses the one with the highest. So in order to get the probability of the current outcome, you need to do something like this.

results = classifier.predict(input_fn = lambda: mem_input_fn())

for r in results:
    idx = r["classes"][0] # idx is the predicted label
    print idx, r["probabilities"][int(idx)]