On Fri, 2021-09-10 at 14:51 -0600, Aaron Meurer wrote:
> On Thu, Sep 9, 2021 at 7:11 PM Sebastian Berg
> wrote:
> >
> > On Sun, 2021-09-05 at 21:08 +0200, Ralf Gommers wrote:
> > > On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar <
> > > kshitijkalambar...@gmail.com> wrote:
> > >
> > > > Hi,
On Thu, Sep 9, 2021 at 7:11 PM Sebastian Berg
wrote:
>
> On Sun, 2021-09-05 at 21:08 +0200, Ralf Gommers wrote:
> > On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar <
> > kshitijkalambar...@gmail.com> wrote:
> >
> > > Hi,
> > >
> > > np.trunc returns floating dtype output even for integral dtyp
On Sun, 2021-09-05 at 21:08 +0200, Ralf Gommers wrote:
> On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar <
> kshitijkalambar...@gmail.com> wrote:
>
> > Hi,
> >
> > np.trunc returns floating dtype output even for integral dtype
> > input. As
> > per array-api, it should preserve the input dtyp
On Sat, Sep 4, 2021 at 2:03 AM Kshitij Kalambarkar
wrote:
>
> Hi,
>
> np.trunc returns floating dtype output even for integral dtype input. As per
> array-api, it should preserve the input dtype.
>
> Note: This is also true for np.rint, np.fix, np.ceil, np.floor
Probably worth noting that np.rou
On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar <
kshitijkalambar...@gmail.com> wrote:
> Hi,
>
> np.trunc returns floating dtype output even for integral dtype input. As
> per array-api, it should preserve the input dtype.
>
Just a note that it's not compatibility with the array API standard
Hi,
np.trunc returns floating dtype output even for integral dtype input. As
per array-api, it should preserve the input dtype.
Note: This is also true for np.rint, np.fix, np.ceil, np.floor
Reference: https://github.com/numpy/numpy/issues/19464
Possible Fix:
1. We update the behaviour directly
