zoo/resnet/resnet_cifar10_v2_c.py
def learner(self, x, **metaparameters):
        """ Construct the Learner
            x        : input to the learner
            groups   : filter/blocks per group
        """
        groups = metaparameters['groups']

        # first group uses strides=1 for first convolution
        x = self.group(x, **groups.pop(0), expand=4)

        # remaining greoups
        for group in groups:
            x = self.group(x, **group, expand=2)

        return x
 Construct the Learner
            x        : input to the learner
            groups   : filter/blocks per group
        
Construct the Learner
x        : input to the learner
groups   : filter/blocks per group
Construct the Learner x : input to the learner groups : filter / blocks per group
def learner(self, x, **metaparameters):
        groups = metaparameters['groups']
        x = self.group(x, **groups.pop(0), expand=4)
        for group in groups:
            x = self.group(x, **group, expand=2)
        return x
def learner ( self , x , ** metaparameters ) : groups = metaparameters [ 'groups' ] x = self . group ( x , ** groups . pop ( 0 ) , expand = 4 ) for group in groups : x = self . group ( x , ** group , expand = 2 ) return x
Construct the Learner
x        : input to the learner
groups   : filter/blocks per group
Construct the Learner x : input to the learner groups : filter / blocks per group
""" Construct the Learner
            x        : input to the learner
            groups   : filter/blocks per group
        """ # first group uses strides=1 for first convolution # remaining greoups
self
x