zoo/vgg/vgg_c.py
def example():
    ''' Example for constructing/training a VGG model on CIFAR-10
    '''
    # Example of constructing a mini-VGG
    groups = [ { 'n_layers': 1, 'n_filters': 64 },
               { 'n_layers': 2, 'n_filters': 128 },
               { 'n_layers': 2, 'n_filters': 256 } ]
    vgg = VGG(groups, input_shape=(32, 32, 3), n_classes=10)
    vgg.model.summary()

    # train on CIFAR-10
    vgg.cifar10()
 Example for constructing/training a VGG model on CIFAR-10
    
Example for constructing/training a VGG model on CIFAR-10
Example for constructing / training a VGG model on CIFAR - 10
def example():
    groups = [ { 'n_layers': 1, 'n_filters': 64 },
               { 'n_layers': 2, 'n_filters': 128 },
               { 'n_layers': 2, 'n_filters': 256 } ]
    vgg = VGG(groups, input_shape=(32, 32, 3), n_classes=10)
    vgg.model.summary()
    vgg.cifar10()
def example ( ) : groups = [ { 'n_layers' : 1 , 'n_filters' : 64 } , { 'n_layers' : 2 , 'n_filters' : 128 } , { 'n_layers' : 2 , 'n_filters' : 256 } ] vgg = VGG ( groups , input_shape = ( 32 , 32 , 3 ) , n_classes = 10 ) vgg . model . summary ( ) vgg . cifar10 ( )
Example for constructing/training a VGG model on CIFAR-10
Example for constructing / training a VGG model on CIFAR - 10
''' Example for constructing/training a VGG model on CIFAR-10
    ''' # Example of constructing a mini-VGG # train on CIFAR-10