Can we use tf.spectral fourier functions in keras?

Question

Let us start with an input that is a simple time series and try to build an autoencoder that simply fourier transforms then untransforms our data in keras.

If we try to

Answer 1

I stumbled upon this as I was trying to solve the same problem. You can make the transition lossless by wrapping tf.real and tf.imag into Lambda layers (I'm using stft because there's no real valued equivalent):

x = tf.keras.layers.Lambda(
    lambda v: tf.signal.stft(
        v,
        frame_length=1024,
        frame_step=256,
        fft_length=1024,
    ), name='gen/FFTLayer')(inputs)
real = tf.keras.layers.Lambda(tf.real)(x)
imag = tf.keras.layers.Lambda(tf.imag)(x)
...
# transform real and imag either separately or by concatenating them in the feature space.
...
x = tf.keras.layers.Lambda(lambda x: tf.complex(x[0], x[1]))([real, imag])
x = tf.keras.layers.Lambda(
    lambda v: tf.signal.inverse_stft(
        v,
        frame_length=1024,
        frame_step=256,
        fft_length=1024,
    ))(x)