is a `tf.data.Dataset`-based replacement of the legacy
        `TimeseriesGenerator`. It takes you from an array of timeseries data to
        a dataset of shifting windows with their targets.
*   Added
    [`experimental_steps_per_execution`](https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/Model?hl=en#compile)

significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need to reduce every time we shift. i := len(x.limbs) - 1 // For the first N - 1 limbs we can skip the actual shifting and position // them at the shifted position, which starts at min(N - 2, i). start := len(m.nat.limbs)...

significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need to reduce every time we shift. i := len(x.limbs) - 1 // For the first N - 1 limbs we can skip the actual shifting and position // them at the shifted position, which starts at min(N - 2, i). start := len(m.nat.limbs)...

1F266..1F2FF  ; disallowed                             # NA   <reserved-1F266>..<reserved-1F2FF>
1F300..1F320  ; valid                  ;      ; NV8    # 6.0  CYCLONE..SHOOTING STAR
1F321..1F32C  ; valid                  ;      ; NV8    # 7.0  THERMOMETER..WIND BLOWING FACE
1F32D..1F32F  ; valid                  ;      ; NV8    # 8.0  HOT DOG..BURRITO