def call()

in realbook/layers/math.py [0:0]

• 12 lines of code
• 1 McCabe index (conditional complexity)

    def call(self, inputs: tf.Tensor) -> tf.Tensor:
        inputs = self.squeeze_batch(inputs)  # type: ignore
        # convert magnitude to power
        power = tf.math.square(inputs)
        log_power = 10 * log_base_b(power + 1e-10, 10)

        log_power_min = tf.reshape(tf.math.reduce_min(log_power, axis=[1, 2]), [tf.shape(inputs)[0], 1, 1])
        log_power_offset = log_power - log_power_min
        log_power_offset_max = tf.reshape(
            tf.math.reduce_max(log_power_offset, axis=[1, 2]),
            [tf.shape(inputs)[0], 1, 1],
        )
        log_power_normalized = tf.math.divide_no_nan(log_power_offset, log_power_offset_max)

        return tf.reshape(log_power_normalized, tf.shape(inputs))