zoo/srcnn/srcnn_c.py
def encoder(self, x, f2):
        """ Construct the Encoder
            x  : the input to the encoder
            f2 : the filter size
        """
        # n2, 1x1 bottleneck convolution
        x = self.Conv2D(x, 32, (f2, f2), padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        return x
 Construct the Encoder
            x  : the input to the encoder
            f2 : the filter size
        
Construct the Encoder
x  : the input to the encoder
f2 : the filter size
Construct the Encoder x : the input to the encoder f2 : the filter size
def encoder(self, x, f2):
        x = self.Conv2D(x, 32, (f2, f2), padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        return x
def encoder ( self , x , f2 ) : x = self . Conv2D ( x , 32 , ( f2 , f2 ) , padding = 'same' ) x = self . BatchNormalization ( x ) x = self . ReLU ( x ) return x
Construct the Encoder
x  : the input to the encoder
f2 : the filter size
Construct the Encoder x : the input to the encoder f2 : the filter size
""" Construct the Encoder
            x  : the input to the encoder
            f2 : the filter size
        """ # n2, 1x1 bottleneck convolution
self
x
f2