Hi,
I’m quite lost with the alpaca model. I guess I’m not understanding the Functional API or maybe my Python level is not good enough.
I understand what I want to do but I’m totally lost with the syntax.
For instance, data augmentation: How am I supposed to proceed?
# apply data augmentation to the inputs
inputs = data_augmentation(inputs)
Will this apply the data_augmentation to input of the model?
Then the x in the pre-code…
x = preprocess_input(None)
# set training to False to avoid keeping track of statistics in the batch norm layer
x = base_model(None, training=None)
# add the new Binary classification layers
# use global avg pooling to summarize the info in each channel
x = None()(x)
# include dropout with probability of 0.2 to avoid overfitting
x = None(None)(x)
Are this x to be changed by something else by me or is it a real variable x to be later processed?
Is there open hours to support with questions like this one?
Thxs!