zoo/srcnn/srcnn_c.py
def reconstruction(self, x, f3):
        """ Construct the Encoder
            x  : the input to the reconstruction
            f3 : the filter size
        """
        # n3, reconstruction convolution
        x = self.Conv2D(x, 3, (f3, f3), padding='same')
        x = self.BatchNormalization(x)
        outputs = Activation('sigmoid')(x)
        return outputs
 Construct the Encoder
            x  : the input to the reconstruction
            f3 : the filter size
        
Construct the Encoder
x  : the input to the reconstruction
f3 : the filter size
Construct the Encoder x : the input to the reconstruction f3 : the filter size
def reconstruction(self, x, f3):
        x = self.Conv2D(x, 3, (f3, f3), padding='same')
        x = self.BatchNormalization(x)
        outputs = Activation('sigmoid')(x)
        return outputs
def reconstruction ( self , x , f3 ) : x = self . Conv2D ( x , 3 , ( f3 , f3 ) , padding = 'same' ) x = self . BatchNormalization ( x ) outputs = Activation ( 'sigmoid' ) ( x ) return outputs
Construct the Encoder
x  : the input to the reconstruction
f3 : the filter size
Construct the Encoder x : the input to the reconstruction f3 : the filter size
""" Construct the Encoder
            x  : the input to the reconstruction
            f3 : the filter size
        """ # n3, reconstruction convolution
self
x
f3