zoo/srcnn/srcnn_c.py
def stem(self, inputs, f1):
        """ Construct the Stem Convolutional Group 
            inputs : the input tensor
            f1     : filter size
        """
        # n1, dimensionality expansion with large coarse filter
        x = self.Conv2D(inputs, 64, (f1, f1), padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        return x
 Construct the Stem Convolutional Group 
            inputs : the input tensor
            f1     : filter size
        
Construct the Stem Convolutional Group
inputs : the input tensor
f1     : filter size
Construct the Stem Convolutional Group inputs : the input tensor f1 : filter size
def stem(self, inputs, f1):
        x = self.Conv2D(inputs, 64, (f1, f1), padding='same')
        x = self.BatchNormalization(x)
        x = self.ReLU(x)
        return x
def stem ( self , inputs , f1 ) : x = self . Conv2D ( inputs , 64 , ( f1 , f1 ) , padding = 'same' ) x = self . BatchNormalization ( x ) x = self . ReLU ( x ) return x
Construct the Stem Convolutional Group
inputs : the input tensor
f1     : filter size
Construct the Stem Convolutional Group inputs : the input tensor f1 : filter size
""" Construct the Stem Convolutional Group 
            inputs : the input tensor
            f1     : filter size
        """ # n1, dimensionality expansion with large coarse filter
self
inputs
f1