import tensorflow as tf

            return logits, prediction
    def general_conv2d(self, input_data, filters = 64,  kernel_size = 7, stride = 1, stddev = 0.02, activation_function = "relu", padding = "VALID", do_norm=True, relu_factor = 0, name="conv2d"):
        with tf.variable_scope(name):
            conv = tf.layers.conv2d(input_data, filters, kernel_size, stride, padding, activation=None)
