Getting started
Getting started with the new torch.fft module is easy whether you are familiar with NumPy’s np.fft module or not. While complete documentation for each function in the module can be found here, a breakdown of what it offers is:

fft, which computes a complex FFT over a single dimension, and ifft, its inverse
the more general fftn and ifftn, which support multiple dimensions
The “real” FFT functions, rfft, irfft, rfftn, irfftn,  designed to work with signals that are real-valued in their time domains
The "Hermitian" FFT functions, hfft and ihfft, designed to work with signals that are real-valued in their frequency domains
Helper functions, like fftfreq, rfftfreq, fftshift, ifftshift, that make it easier to manipulate signals
