Function as argument in alpaca_model function

Hi folks!

In the second programming assignment of Week 2, the function alpaca_model receives a function as a parameter. The default value for it is “data_augmenter()”

When I try to use the parameter in order to “apply data augmentation to the inputs” the test fails:

x = data_augmentation(inputs)

['Sequential', (None, 160, 160, 3), 0] 

 does not match the input value: 

 ['Sequential', (None, None, 160, None), 0]

But if call the function directly it works just fine:

x = data_augmenter()(inputs)

All tests passed!
['InputLayer', [(None, 160, 160, 3)], 0]
['Sequential', (None, 160, 160, 3), 0]
['TensorFlowOpLayer', [(None, 160, 160, 3)], 0]
['TensorFlowOpLayer', [(None, 160, 160, 3)], 0]
['Functional', (None, 5, 5, 1280), 2257984]
['GlobalAveragePooling2D', (None, 1280), 0]
['Dropout', (None, 1280), 0, 0.2]
['Dense', (None, 1), 1281, 'linear']

What am I missing here?

1 Like

Hi rogeriovazp,

The test is based on model2, which is defined just below the function alpaca_model. model2 takes the global variable data_augmentation as a parameter, which was defined in cell 7, two cells below the function data_augmenter().

Could it be that you made some changes to the function data_augmenter() after having run cell 7, and did not rerun cell 7? That could explain it.

A way to find out is to rerun cell 7 and then try with x = data_augmentation(inputs). You could also try to rerun all cells up to and including the test and see if it passes this time.


That was it! Everything is running smoothly now. Thank you so much!