zoo/siamese_twin/siamese_twin_c.py
def stem(inputs):
            ''' Construct the Stem Group
                inputs: the input tensor
            '''

            # entry convolutional layer and reduce feature maps by 75% (max pooling)
            x = self.Conv2D(inputs, 64, (10, 10), activation='relu', kernel_initializer=conv_weights, bias_initializer=biases)
            x = MaxPooling2D((2, 2), strides=2)(x)
            return x
 Construct the Stem Group
                inputs: the input tensor
            
Construct the Stem Group
inputs: the input tensor
Construct the Stem Group inputs : the input tensor
def stem(inputs):
            x = self.Conv2D(inputs, 64, (10, 10), activation='relu', kernel_initializer=conv_weights, bias_initializer=biases)
            x = MaxPooling2D((2, 2), strides=2)(x)
            return x
def stem ( inputs ) : x = self . Conv2D ( inputs , 64 , ( 10 , 10 ) , activation = 'relu' , kernel_initializer = conv_weights , bias_initializer = biases ) x = MaxPooling2D ( ( 2 , 2 ) , strides = 2 ) ( x ) return x
Construct the Stem Group
inputs: the input tensor
Construct the Stem Group inputs : the input tensor
''' Construct the Stem Group
                inputs: the input tensor
            ''' # entry convolutional layer and reduce feature maps by 75% (max pooling)
inputs