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
compute `input` is odd, it should be provided since it cannot be inferred
properly.

*   Add a bitwise module with bitwise_and, bitwise_or, bitwise_xor, and invert
    functions.
*   Add fixed-grid ODE integration routines.
*   Allow passing bounds to ScipyOptimizerInterface.
*   Correctness fixes for fft_length parameter to `tf.spectral.rfft` &
    `tf.spectral.irfft`.
*   Exported model signatures using the 'predict' method will no longer have
    their input and output keys silently ignored and rewritten to 'inputs' and