fft

torch_to_nnef.op.aten.fft

fft_fft

fft_fft(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_fft' to NNEF.

fft_fftn

fft_fftn(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_fftn' to NNEF (forward N-dim FFT).

fft_ifft

fft_ifft(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_ifft' to NNEF.

fft_ifftn

fft_ifftn(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_ifftn' to NNEF (inverse N-dim FFT).

fft_irfft

fft_irfft(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_irfft' to NNEF.

One-sided complex spectrum -> real signal of length n (defaults to 2 * (K - 1) where K = input.shape[dim]). Reconstruct the Hermitian-symmetric full spectrum: take the slice [1, K-1), reverse it on dim, conjugate (negate imag), concat after the input -> (..., n, 2); run an inverse FFT; divide by n; drop the imaginary part.

fft_rfft

fft_rfft(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:fft_rfft' to NNEF.

Real input -> one-sided complex spectrum on dim. Mirrors fft_fft (pad to complex, run tract_core_fft) then slices the FFT axis to the first N // 2 + 1 bins.

stft

stft(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:stft' to NNEF.