Hi vaibhavpatel1,
I had the same problem. It is necessary to pass the inputs to the data augmentation and then the output to the preprocessing.
You can also check here for help
“x = data_ augmenter()” is wrong on two counts.
- It’s not the correct function name.
- You didn’t pass any data argument.
but data_augmenter don’t take any arguments when I defined it.
def data_augmenter():
‘’’
Create a Sequential model composed of 2 layers
Returns:
tf.keras.Sequential
‘’’
### START CODE HERE
data_augmentation = tf.keras.Sequential()
data_augmentation.add(RandomFlip(‘horizontal’))
data_augmentation.add(RandomRotation(0.2))
### END CODE HERE
return data_augmentation
That code doesn’t contain the data - it just defines the layer. You still have to pass some data to the layer.
But you’re not supposed to use “data_augmenter()” at all.
The instructions say to use “data augmentation”. They provide a helper function by that name.
thank you so much i passed