zoo/siamese_twin/siamese_twin_c.py
def classifier(x):
            ''' Construct the classifier (Encoding block) 
                x  : input to the classifier
            '''

            # flatten the maps into a 1D vector
            x = Flatten()(x)
    
            # use dense layer to produce a 4096 encoding of the flattened feature maps
            x = self.Dense(x, 4096, activation='sigmoid', kernel_initializer=dense_weights, bias_initializer=biases)
            return x
 Construct the classifier (Encoding block) 
                x  : input to the classifier
            
Construct the classifier (Encoding block)
x  : input to the classifier
Construct the classifier ( Encoding block ) x : input to the classifier
def classifier(x):
            x = Flatten()(x)
            x = self.Dense(x, 4096, activation='sigmoid', kernel_initializer=dense_weights, bias_initializer=biases)
            return x
def classifier ( x ) : x = Flatten ( ) ( x ) x = self . Dense ( x , 4096 , activation = 'sigmoid' , kernel_initializer = dense_weights , bias_initializer = biases ) return x
Construct the classifier (Encoding block)
x  : input to the classifier
Construct the classifier ( Encoding block ) x : input to the classifier
''' Construct the classifier (Encoding block) 
                x  : input to the classifier
            ''' # flatten the maps into a 1D vector # use dense layer to produce a 4096 encoding of the flattened feature maps
x