nvmath.fft.rfft

nvmath.fft.rfft(operand, axes=None, options=None, prolog=None, epilog=None, stream=None)[source]

Perform an N-D real-to-complex (R2C) FFT on the provided real operand.

Parameters:

  • operand – A tensor (ndarray-like object). The currently supported types are numpy.ndarray, cupy.ndarray, and torch.Tensor.

  • axes – The dimensions along which the FFT is performed. Currently, it is required that the axes are contiguous and include the first or the last dimension. Only up to 3D FFTs are supported.

  • options – Specify options for the FFT as a FFTOptions object. Alternatively, a dict containing the parameters for the FFTOptions constructor can also be provided. If not specified, the value will be set to the default-constructed FFTOptions object.

  • prolog – Provide device-callable function in LTO-IR format to use as load-callback as an object of type DeviceCallable. Alternatively, a dict containing the parameters for the DeviceCallable constructor can also be provided. The default is no prolog.

  • epilog – Provide device-callable function in LTO-IR format to use as store-callback as an object of type DeviceCallable. Alternatively, a dict containing the parameters for the DeviceCallable constructor can also be provided. The default is no epilog.

  • stream – Provide the CUDA stream to use for executing the operation. Acceptable inputs include cudaStream_t (as Python int), cupy.cuda.Stream, and torch.cuda.Stream. If a stream is not provided, the current stream from the operand package will be used.

Returns:

A complex tensor that remains on the same device and belongs to the same package as the input operand. The extent of the last transformed axis in the result will be operand.shape[axes[-1]] // 2 + 1.

See also

fft(), irfft(), FFT.