zoo/xception/xception_c.py
def stem(inputs):
            """ Create the stem entry into the neural network
                inputs : input tensor to neural network
            """
            # Strided convolution - dimensionality reduction
            # Reduce feature maps by 75%
            x = self.Conv2D(inputs, 32, (3, 3), strides=(2, 2), **metaparameters)
            x = self.BatchNormalization(x)
            x = self.ReLU(x)

            # Convolution - dimensionality expansion
            # Double the number of filters
            x = self.Conv2D(x, 64, (3, 3), strides=(1, 1), **metaparameters)
            x = self.BatchNormalization(x)
            x = self.ReLU(x)
            return x
 Create the stem entry into the neural network
                inputs : input tensor to neural network
            
Create the stem entry into the neural network
inputs : input tensor to neural network
Create the stem entry into the neural network inputs : input tensor to neural network
def stem(inputs):
            x = self.Conv2D(inputs, 32, (3, 3), strides=(2, 2), **metaparameters)
            x = self.BatchNormalization(x)
            x = self.ReLU(x)
            x = self.Conv2D(x, 64, (3, 3), strides=(1, 1), **metaparameters)
            x = self.BatchNormalization(x)
            x = self.ReLU(x)
            return x
def stem ( inputs ) : x = self . Conv2D ( inputs , 32 , ( 3 , 3 ) , strides = ( 2 , 2 ) , ** metaparameters ) x = self . BatchNormalization ( x ) x = self . ReLU ( x ) x = self . Conv2D ( x , 64 , ( 3 , 3 ) , strides = ( 1 , 1 ) , ** metaparameters ) x = self . BatchNormalization ( x ) x = self . ReLU ( x ) return x
Create the stem entry into the neural network
inputs : input tensor to neural network
Create the stem entry into the neural network inputs : input tensor to neural network
""" Create the stem entry into the neural network
                inputs : input tensor to neural network
            """ # Strided convolution - dimensionality reduction # Reduce feature maps by 75% # Convolution - dimensionality expansion # Double the number of filters
inputs