Align keepdims docstring (state None value)

Author: antonwolfy

dpnp/dpnp_iface_logic.py

@@ -103,7 +103,7 @@ def all(a, /, axis=None, out=None, keepdims=False, *, where=True):
         the same shape as the expected output but the type (of the returned
         values) will be cast if necessary.
         Default: ``None``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If ``True``, the reduced axes (dimensions) are included in the result
         as singleton dimensions, so that the returned array remains
         compatible with the input array according to Array Broadcasting
@@ -275,7 +275,7 @@ def any(a, /, axis=None, out=None, keepdims=False, *, where=True):
         the same shape as the expected output but the type (of the returned
         values) will be cast if necessary.
         Default: ``None``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If ``True``, the reduced axes (dimensions) are included in the result
         as singleton dimensions, so that the returned array remains
         compatible with the input array according to Array Broadcasting

dpnp/dpnp_iface_nanfunctions.py

@@ -682,7 +682,7 @@ def nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=False):
        but it will probably be fully or partially sorted.
 
        Default: ``False``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If ``True``, the reduced axes (dimensions) are included in the result
         as singleton dimensions, so that the returned array remains
         compatible with the input array according to Array Broadcasting

dpnp/dpnp_iface_statistics.py

@@ -1125,7 +1125,7 @@ def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):
        but it will probably be fully or partially sorted.
 
        Default: ``False``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If ``True``, the reduced axes (dimensions) are included in the result
         as singleton dimensions, so that the returned array remains
         compatible with the input array according to Array Broadcasting

dpnp/linalg/dpnp_iface_linalg.py

@@ -962,7 +962,7 @@ def matrix_norm(x, /, *, keepdims=False, ord="fro"):
     x : {dpnp.ndarray, usm_ndarray}
         Input array having shape (..., M, N) and whose two innermost
         dimensions form ``MxN`` matrices.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If this is set to ``True``, the axes which are normed over are left in
         the result as dimensions with size one. With this option the result
         will broadcast correctly against the original `x`.
@@ -1290,7 +1290,7 @@ def norm(x, ord=None, axis=None, keepdims=False):
         `x` is 1-D) or a matrix norm (when `x` is 2-D) is returned.
 
         Default: ``None``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If this is set to ``True``, the axes which are normed over are left in
         the result as dimensions with size one. With this option the result
         will broadcast correctly against the original `x`.
@@ -2336,7 +2336,7 @@ def vector_norm(x, /, *, axis=None, keepdims=False, ord=2):
         equivalent to computing the vector norm of a flattened array).
 
         Default: ``None``.
-    keepdims : bool, optional
+    keepdims : {None, bool}, optional
         If this is set to ``True``, the axes which are normed over are left in
         the result as dimensions with size one. With this option the result
         will broadcast correctly against the original `x`.