zoo/vgg/vgg_c.py
def learner(self, x, **metaparameters):
        """ Construct the (Feature) Learner
            x        : input to the learner
            blocks   : list of groups: filter size and number of conv layers
        """ 
        blocks = metaparameters['blocks']

        # The convolutional groups
        for block in blocks:
            x = self.group(x, **block, **metaparameters)
        return x
 Construct the (Feature) Learner
            x        : input to the learner
            blocks   : list of groups: filter size and number of conv layers
        
Construct the (Feature) Learner
x        : input to the learner
blocks   : list of groups: filter size and number of conv layers
Construct the ( Feature ) Learner x : input to the learner blocks : list of groups : filter size and number of conv layers
def learner(self, x, **metaparameters):
        blocks = metaparameters['blocks']
        for block in blocks:
            x = self.group(x, **block, **metaparameters)
        return x
def learner ( self , x , ** metaparameters ) : blocks = metaparameters [ 'blocks' ] for block in blocks : x = self . group ( x , ** block , ** metaparameters ) return x
Construct the (Feature) Learner
x        : input to the learner
blocks   : list of groups: filter size and number of conv layers
Construct the ( Feature ) Learner x : input to the learner blocks : list of groups : filter size and number of conv layers
""" Construct the (Feature) Learner
            x        : input to the learner
            blocks   : list of groups: filter size and number of conv layers
        """ # The convolutional groups
self
x