er. (Didn't
read it before starting writing this.) Quite a lot of interesting
discussions, especially the legacy argument.
BR Oscar Gustafsson
(FWIW, I suggested that NumPy should be able to round to a given number of
bits, or arbitrary base, primarily as a way to fake (short) fixed-point
repr
should be noted that this is not a suitable replacement if you just
want to use a different, existing, dtype, e.g. from ml_dtypes, this is a
completely flexible solution for any dtype with complete control of
rounding/quantization, including stochastic quantization.
BR Oscar Gustafsson
(I will not
. Provide a separate function (binaryround?)
2. Provide a base argument to around which defaults to 10.
3. Provide a quant(ization) function where the argument is the step-size.
(For completeness, one may think of having multiple quantization modes, not
just rounding)
Any opinions?
BR Oscar Gustafsson
Den tis 8 nov. 2022 kl 11:44 skrev Sebastian Berg <
sebast...@sipsolutions.net>:
> On Thu, 2022-11-03 at 11:37 +0100, Oscar Gustafsson wrote:
> > Hi all,
> >
> > I hope this is the correct way to propose a new feature.
> > https://github.com/numpy/numpy/is
he quant function,
https://www.mathworks.com/help/deeplearning/ref/quant.html which basically
supports arbitrary bases (as a special case of an even more general
approach). So there may be other use cases (although the example basically
just implements around(x, 1)).
BR
Den tors 10 nov. 2022 kl 13:10 skrev Sebastian Berg <
sebast...@sipsolutions.net>:
> On Thu, 2022-11-10 at 11:08 +0100, Oscar Gustafsson wrote:
> > >
> > > I'm not an expert, but I never encountered rounding floating point
> > > numbers
> > >
the spring, so
primarily asking for planning and describing the project a bit better.
BR Oscar
Den tors 10 nov. 2022 kl 15:13 skrev Sebastian Berg <
sebast...@sipsolutions.net>:
> On Thu, 2022-11-10 at 14:55 +0100, Oscar Gustafsson wrote:
> > Den tors 10 nov. 2022 kl 13:10 skrev Se
