Lines Matching full:norm

43     x: TensorLikeType, norm: NormType, signal_numel: int, forward: bool
46     torch._check(norm in _NORM_VALUES, lambda: f"Invalid normalization mode: {norm}")
48     if norm == "ortho":
51     normalize = (not forward and (norm is None or norm == "backward")) or (
52         forward and norm == "forward"
121     norm: NormType,
140     return _apply_norm(output, norm=norm, signal_numel=last_dim_size, forward=forward)
148     norm: NormType,
168     ret = _apply_norm(ret, norm, dim_size, forward)
177     norm: NormType,
195     return _apply_norm(ret, norm, dim_size, forward)
204     norm: NormType = None,
207         return _fft_c2c("fft", input, n, dim, norm, forward=True)
209         return _fft_r2c("fft", input, n, dim, norm, forward=True, onesided=False)
218     norm: NormType = None,
221         return _fft_c2c("ifft", input, n, dim, norm, forward=False)
223         return _fft_r2c("ifft", input, n, dim, norm, forward=False, onesided=False)
232     norm: NormType = None,
234     return _fft_r2c("rfft", input, n, dim, norm, forward=True, onesided=True)
243     norm: NormType = None,
245     return _fft_c2r("irfft", input, n, dim, norm, forward=False)
254     norm: NormType = None,
256     return _fft_c2r("hfft", input, n, dim, norm, forward=True)
265     norm: NormType = None,
267     return _fft_r2c("ihfft", input, n, dim, norm, forward=False, onesided=True)
344     norm: NormType,
355     return _apply_norm(output, norm=norm, signal_numel=_prod(shape), forward=forward)
364     norm: NormType = None,
368     return _fftn_c2c("fftn", x, shape, dim, norm, forward=True)
377     norm: NormType = None,
381     return _fftn_c2c("ifftn", x, shape, dim, norm, forward=False)
390     norm: NormType = None,
400     return _apply_norm(out, norm=norm, signal_numel=_prod(shape), forward=True)
409     norm: NormType = None,
423         tmp = _apply_norm(tmp, norm=norm, signal_numel=shape[0], forward=False)
428     return _apply_norm(tmp, norm=norm, signal_numel=_prod(shape), forward=False)
471     norm: NormType = None,
479     return _apply_norm(out, norm, _prod(out.shape[d] for d in dim), forward=False)
488     norm: NormType = None,
497     tmp = _apply_norm(tmp, norm, _prod(shape[:-1]), forward=True)
500     return _apply_norm(out, norm, last_dim_size, forward=True)
509     norm: NormType = None,
511     return torch.fft.fftn(input, s=s, dim=dim, norm=norm)
520     norm: NormType = None,
522     return torch.fft.ifftn(input, s=s, dim=dim, norm=norm)
531     norm: NormType = None,
533     return torch.fft.rfftn(input, s=s, dim=dim, norm=norm)
542     norm: NormType = None,
544     return torch.fft.irfftn(input, s=s, dim=dim, norm=norm)
553     norm: NormType = None,
555     return torch.fft.hfftn(input, s=s, dim=dim, norm=norm)
564     norm: NormType = None,
566     return torch.fft.ihfftn(input, s=s, dim=dim, norm=norm)