zoo/shufflenet/shufflenet_c.py
def example():
    ''' Example for constructing/training a ShuffleNet model on CIFAR-10
    '''
    # Example of constructing a mini-ShuffleNet
    groups  = [ { 'n_blocks' : 2 }, { 'n_blocks' : 4 } ]
    shufflenet = ShuffleNet(groups, input_shape=(32, 32, 3), n_classes=10)
    shufflenet.model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['acc'])
    shufflenet.model.summary()
    shufflenet.cifar10()
 Example for constructing/training a ShuffleNet model on CIFAR-10
    
Example for constructing/training a ShuffleNet model on CIFAR-10
Example for constructing / training a ShuffleNet model on CIFAR - 10
def example():
    groups  = [ { 'n_blocks' : 2 }, { 'n_blocks' : 4 } ]
    shufflenet = ShuffleNet(groups, input_shape=(32, 32, 3), n_classes=10)
    shufflenet.model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['acc'])
    shufflenet.model.summary()
    shufflenet.cifar10()
def example ( ) : groups = [ { 'n_blocks' : 2 } , { 'n_blocks' : 4 } ] shufflenet = ShuffleNet ( groups , input_shape = ( 32 , 32 , 3 ) , n_classes = 10 ) shufflenet . model . compile ( loss = 'sparse_categorical_crossentropy' , optimizer = 'adam' , metrics = [ 'acc' ] ) shufflenet . model . summary ( ) shufflenet . cifar10 ( )
Example for constructing/training a ShuffleNet model on CIFAR-10
Example for constructing / training a ShuffleNet model on CIFAR - 10
''' Example for constructing/training a ShuffleNet model on CIFAR-10
    ''' # Example of constructing a mini-ShuffleNet