zoo/resnext/resnext_c.py
def example():
    ''' Example for constructing/training a ResNeXt model on CIFAR-10
    '''
    # Example of constructing a mini-ResNeXt
    groups =  [ { 'filters_in': 128,  'filters_out' : 256,  'n_blocks': 1 },
                { 'filters_in': 256,  'filters_out' : 512,  'n_blocks': 2 },
                { 'filters_in': 512,  'filters_out' : 1024, 'n_blocks': 2 } ]
    resnext = ResNeXt(groups, input_shape=(32, 32, 3), n_classes=10)
    resnext.model.summary()
    resnext.cifar10()
 Example for constructing/training a ResNeXt model on CIFAR-10
    
Example for constructing/training a ResNeXt model on CIFAR-10
Example for constructing / training a ResNeXt model on CIFAR - 10
def example():
    groups =  [ { 'filters_in': 128,  'filters_out' : 256,  'n_blocks': 1 },
                { 'filters_in': 256,  'filters_out' : 512,  'n_blocks': 2 },
                { 'filters_in': 512,  'filters_out' : 1024, 'n_blocks': 2 } ]
    resnext = ResNeXt(groups, input_shape=(32, 32, 3), n_classes=10)
    resnext.model.summary()
    resnext.cifar10()
def example ( ) : groups = [ { 'filters_in' : 128 , 'filters_out' : 256 , 'n_blocks' : 1 } , { 'filters_in' : 256 , 'filters_out' : 512 , 'n_blocks' : 2 } , { 'filters_in' : 512 , 'filters_out' : 1024 , 'n_blocks' : 2 } ] resnext = ResNeXt ( groups , input_shape = ( 32 , 32 , 3 ) , n_classes = 10 ) resnext . model . summary ( ) resnext . cifar10 ( )
Example for constructing/training a ResNeXt model on CIFAR-10
Example for constructing / training a ResNeXt model on CIFAR - 10
''' Example for constructing/training a ResNeXt model on CIFAR-10
    ''' # Example of constructing a mini-ResNeXt