Factory

A factory makes objects that compute FFTs.

To avoid needless repetition, only the single precision classes for NumPy are documented below. Of course, float16, float32, float64 and numpy, torch, jax, tensorflow, and dlpack are all similar.

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CLASSES

class hpk.fft.FactoryCC_float32_numpy

FactoryCC_float32_numpy.makeInplace(self, layout: collections.abc.Sequence[hpk.fft.InplaceDim], batch: hpk.fft.InplaceDim = (1, 0)) → hpk.fft.InplaceCC_float32

FactoryCC_float32_numpy.makeOoplace(self, layout: collections.abc.Sequence[hpk.fft.OoplaceDim], batch: hpk.fft.OoplaceDim = (1, 0, 0)) → hpk.fft.OoplaceCC_float32

FactoryCC_float32_numpy.maxThreads(self) → int

An upper bound on the number of threads that could be used.

FactoryCC_float32_numpy.nextFastLayout(self, layout: collections.abc.Sequence[hpk.fft.InplaceDim]) → list[hpk.fft.InplaceDim]

FactoryCC_float32_numpy.nextFastLayout(self, layout: collections.abc.Sequence[hpk.fft.OoplaceDim]) → list[hpk.fft.OoplaceDim]

class hpk.fft.FactoryRC_float32_numpy

FactoryRC_float32_numpy.makeInplace(self, layout: collections.abc.Sequence[hpk.fft.InplaceDim], batch: hpk.fft.InplaceDim = (1, 0)) → hpk.fft.InplaceRC_float32

FactoryRC_float32_numpy.makeOoplace(self, layout: collections.abc.Sequence[hpk.fft.OoplaceDim], batch: hpk.fft.OoplaceDim = (1, 0, 0)) → hpk.fft.OoplaceRC_float32

FactoryRC_float32_numpy.maxThreads(self) → int

An upper bound on the number of threads that could be used.

FactoryRC_float32_numpy.nextFastLayout(self, layout: collections.abc.Sequence[hpk.fft.InplaceDim]) → list[hpk.fft.InplaceDim]

FactoryRC_float32_numpy.nextFastLayout(self, layout: collections.abc.Sequence[hpk.fft.OoplaceDim]) → list[hpk.fft.OoplaceDim]