zoo/shufflenet/shufflenet_c.py
def stem(self, inputs):
        ''' Construct the Stem Convolution Group 
            inputs : input image (tensor)
        '''
        x = self.Conv2D(inputs, 24, (3, 3), strides=2, padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        x = MaxPooling2D((3, 3), strides=2, padding='same')(x)
        return x
 Construct the Stem Convolution Group 
            inputs : input image (tensor)
        
Construct the Stem Convolution Group
inputs : input image (tensor)
Construct the Stem Convolution Group inputs : input image ( tensor )
def stem(self, inputs):
        x = self.Conv2D(inputs, 24, (3, 3), strides=2, padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        x = MaxPooling2D((3, 3), strides=2, padding='same')(x)
        return x
def stem ( self , inputs ) : x = self . Conv2D ( inputs , 24 , ( 3 , 3 ) , strides = 2 , padding = 'same' ) x = self . BatchNormalization ( x ) x = self . ReLU ( x ) x = MaxPooling2D ( ( 3 , 3 ) , strides = 2 , padding = 'same' ) ( x ) return x
Construct the Stem Convolution Group
inputs : input image (tensor)
Construct the Stem Convolution Group inputs : input image ( tensor )
''' Construct the Stem Convolution Group 
            inputs : input image (tensor)
        '''
self
inputs