in early_s in Estimator
    *   Canned Estimators will now use keras optimizers by default. An error
        will be raised if tf.train.Optimizers are used, and you will have to
        switch to tf.keras.optimizers or tf.compat.v1 canned Estimators.
    *   A checkpoint converter for canned Estimators has been provided to
        transition canned Estimators that are warm started from

signal over the inner-most dimension of `input`.

The inner-most dimension of `input` is assumed to be the result of `RFFT`: the
`fft_length / 2 + 1` unique components of the DFT of a real-valued signal. If
`fft_length` is not provided, it is computed from the size of the inner-most
dimension of `input` (`fft_length = 2 * (inner - 1)`). If the FFT length used to