"Polygamma",
      "PopulationCount",
      "Qr",
      "QuantizeAndDequantizeV2",
      "QuantizeAndDequantizeV3",
      "QuantizeAndDequantizeV4",
      "RFFT",
      "RFFT2D",
      "RFFT3D",
      "RGBToHSV",
      "RandomShuffle",
      "RandomStandardNormal",
      "RandomUniform",
      "RandomUniformInt",
      "ReadVariableOp",
      "ReadVariableXlaSplitND",

}

def TF_RFFT3DOp : TF_Op<"RFFT3D", [Pure]> {
  let summary = "3D real-valued fast Fourier transform.";

  let description = [{
Computes the 3-dimensional discrete Fourier transform of a real-valued signal
over the inner-most 3 dimensions of `input`.

Since the DFT of a real signal is Hermitian-symmetric, `RFFT3D` only returns the

    * Added `dtensor.get_default_mesh`, for retrieving the current default mesh under the dtensor context.
    * \*fft\* ops now support dtensors with any layout. Fixed bug in 'fft2d/fft3d', 'ifft2d/ifft3d', 'rfft2d/rfft3d', and 'irfft2d/irfft3d' for sharde input. Refer to this [blog post](https://blog.tensorflow.org/2023/08/distributed-fast-fourier-transform-in-tensorflow.html) for details.

*  `tf.experimental.strict_mode`