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
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âx = data_ augmenter()â is wrong on two counts.
- Itâs not the correct function name.
- You didnât pass any data argument.
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but data_augmenter donât take any arguments when I defined it.
def data_augmenter():
âââ
Create a Sequential model composed of 2 layers
Returns:
tf.keras.Sequential
âââ
### START CODE HERE
data_augmentation = tf.keras.Sequential()
data_augmentation.add(RandomFlip(âhorizontalâ))
data_augmentation.add(RandomRotation(0.2))
### END CODE HERE
return data_augmentationThat code doesnât contain the data - it just defines the layer. You still have to pass some data to the layer.
But youâre not supposed to use âdata_augmenter()â at all.
The instructions say to use âdata augmentationâ. They provide a helper function by that name.
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thank you so much i passed
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