norm implementation

CHANGELOG.md

@@ -1,12 +1,14 @@
 # Pending additions
-
 ## Bug Fixes
 - [#826](https://github.com/helmholtz-analytics/heat/pull/826) Fixed `__setitem__` handling of distributed `DNDarray` values which have a different shape in the split dimension
+- [#846](https://github.com/helmholtz-analytics/heat/pull/846) Fixed an issue in `_reduce_op` when axis and keepdim were set.
+- [#846](https://github.com/helmholtz-analytics/heat/pull/846) Fixed an issue in `min`, `max` where DNDarrays with empty processes can't be computed.
 
 ## Feature Additions
 
 ### Linear Algebra
 - [#840](https://github.com/helmholtz-analytics/heat/pull/840) New feature: `vecdot()`
+- [#846](https://github.com/helmholtz-analytics/heat/pull/846) New features `norm`, `vector_norm`, `matrix_norm`
 ### Manipulations
 - [#829](https://github.com/helmholtz-analytics/heat/pull/829) New feature: `roll`
 - [#853](https://github.com/helmholtz-analytics/heat/pull/853) New Feature: `swapaxes`

heat/core/_operations.py

@@ -419,7 +419,10 @@ def __reduce_op(
     else:
         output_shape = x.gshape
         for dim in axis:
-            partial = partial_op(partial, dim=dim, keepdim=True)
+            if not (
+                partial.shape.numel() == 0 and partial_op.__name__ in ("local_max", "local_min")
+            ):  # no neutral element for max/min
+                partial = partial_op(partial, dim=dim, keepdim=True)
             output_shape = output_shape[:dim] + (1,) + output_shape[dim + 1 :]
         if not keepdim and not len(partial.shape) == 1:
             gshape_losedim = tuple(x.gshape[dim] for dim in range(len(x.gshape)) if dim not in axis)
@@ -439,7 +442,7 @@ def __reduce_op(
             balanced = True
             if x.comm.is_distributed():
                 x.comm.Allreduce(MPI.IN_PLACE, partial, reduction_op)
-        elif axis is not None:
+        elif axis is not None and not keepdim:
             down_dims = len(tuple(dim for dim in axis if dim < x.split))
             split -= down_dims
             balanced = x.balanced