import tensorflow as tf

        x = self.input_tensor

        x = tf.pad(x, [[0, 0], [3, 3], [3, 3], [0, 0]], 'CONSTANT')

        x = self.__conv2d("conv_1", x, filter_depth=64,
                          kernel_size=7, stride=2, padding='valid')

        x = self.__batch_norm("bn_1", x)
        x = tf.nn.relu(x)

        x = tf.keras.layers.MaxPool2D(pool_size = 3, strides = 2, padding = 'same')(x)

        x = self.__conv_block(stage=0, block=0, inputs=x,
                              filter_depths=[32, 32, 128],
                              kernel_size=3, stride=1)

