[GitHub] [incubator-mxnet] sxjscience opened a new issue #18805: [Numpy] Whether to support 'exclude' flag in numpy operators

[GitBox <gi...@apache.org>]

sxjscience opened a new issue #18805:
URL: https://github.com/apache/incubator-mxnet/issues/18805


   In the old ndarray API, we support `mx.nd.mean(x, axis=1, exclude=True)`, in which the meaning is to sum up the axes except `axis=1`. We do not have the `exclude` option in `mx.np.mean()` so it will be good to have.
   
   See the following code snippet for an example:
   
   https://github.com/apache/incubator-mxnet/blob/74430a92f5232808a169c9e238a419789a5c2fda/python/mxnet/gluon/loss.py#L149-L152
   
   Another option is to directly switch to use DeferedCompute so there is no need to add this option.


----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [incubator-mxnet] szha commented on issue #18805: [Numpy] Whether to support 'exclude' flag in numpy operators

[GitBox <gi...@apache.org>]

szha commented on issue #18805:
URL: https://github.com/apache/incubator-mxnet/issues/18805#issuecomment-670828174


   While this design made a difference when we needed to program in the symbolic way, since in 2.0 the array interface provides eager type inference, our array can behave just like numpy ndarray so this design shouldn't be required anymore. As such, I'm leaning towards that it's still better to be as consistent with the numpy API as possible in the `np` module.


----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

For queries about this service, please contact Infrastructure at:
users@infra.apache.org