message: Added TF.RFFT to TF dialect.
diff: @@ -3144,6 +3144,35 @@ tensor, so its value can change during training.
  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
  }
  +def TF_RFFTOp : TF_Op<"RFFT", [NoSideEffect]> {
  + let summary = "Real-valued fast Fourier transform.";
  +
  + let description = [{
  +Computes the 1-dimensional discrete Fourier transform of a real-valued signal
  +over the inner-most dimension of `input`.
  +
  +Since the DFT of a real signal is Hermitian-symmetric, `RFFT` only returns the
  +`fft_length / 2 + 1` unique components of the FFT: the zero-frequency term,
  +followed by the `fft_length / 2` positive-frequency terms.
  +
  +Along the axis `RFFT` is computed on, if `fft_length` is smaller than the
  +corresponding dimension of `input`, the dimension is cropped. If it is larger,
  +the dimension is padded with zeros.
  + }];
  +
  + let arguments = (ins
  + TF_F32OrF64Tensor:$input,
  + I32Tensor:$fft_length
  + );
  +
  + let results = (outs
  + TensorOf<[TF_Complex128, TF_Complex64]>:$output
  + );
  +
  + TF_DerivedOperandTypeAttr Treal = TF_DerivedOperandTypeAttr<0>;
  + TF_DerivedResultTypeAttr Tcomplex = TF_DerivedResultTypeAttr<0>;
  +}
  +
  def TF_RandomUniformOp : TF_Op<"RandomUniform", []> {
  let summary = "Outputs random values from a uniform distribution.";
  