TypeError: 'numpy.float64' object is not iterable Keras

Question

The following line of code gives me the above error in Keras. model is a Graph model in Keras.

score, acc = model.evaluate({
    'input1': X_test1,
    'input2': X_test2,
    'output':Y_test}, batch_size=450)

but when I change it to the following, it runs fine.

predictions = model.predict({
    'input1': X_test1,
    'input2': X_test2}, batch_size=450)['output']

The Y_test here is a <type 'numpy.ndarray'> of <type 'numpy.ndarray'>. A one-hot encoded vector.

Sample Y_test:

[[1.,0.,0.],[1.,0.,0.],[0.,0.,1.]]

Marcin Możejko · Accepted Answer · 2016-04-11 19:00:40Z

10

As you can see here :

https://github.com/fchollet/keras/blob/master/keras/engine/training.py

The evaluate method returns only test loss (or losses). So assigning result of this method to a pair results in error.

answered Apr 11, 2016 at 19:00

Marcin Możejko

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3 Comments

a'- Over a year ago

Thank you, for pointing that out. It seemed to work fine for the Sequential model, but now I am guessing that it returns two metrics.

Shadi Over a year ago

Actually, it returns the test loss and any metrics requested. Assigning the result to a pair score, acc would have worked had the accuracy metric been requested from the model fitting

Marcin Możejko Over a year ago

This is an quite old answer. Keras changed a lot since this time.

William Collishaw · Accepted Answer · 2016-04-15 06:50:37Z

0

Using keras 1.0 I was able to get the score print out but I would receive this error when I tried to get the score and accuracy.

I downgraded my keras to 0.3.3, and ran the exact same code. I was able to get score and accuracy doing this.

answered Apr 15, 2016 at 6:50

William Collishaw

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