ENH: Improve array function overhead by using vectorcall

This moves dispatching for `__array_function__` into a C-wrapper.  This
helps speed for multiple reasons:
* Avoids one additional dispatching function call to C
* Avoids the use of `*args, **kwargs` which is slower.
* For simple NumPy calls we can stay in the faster "vectorcall" world

This speeds up things generally a little, but can speed things up a lot
when keyword arguments are used on lightweight functions, for example::

    np.can_cast(arr, dtype, casting="same_kind")

is more than twice as fast with this.

There is one alternative in principle to get best speed:  We could inline
the "relevant argument"/dispatcher extraction.  That changes behavior in
an acceptable but larger way (passes default arguments).
Unless the C-entry point seems unwanted, this should be a decent step
in the right direction even if we want to do that eventually, though.

Closes gh-20790
Closes gh-18547  (although not quite sure why)

1 files changed, 4 insertions, 16 deletions

diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index dcb4ed46c..ed4f98704 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -155,10 +155,6 @@ def flipud(m):
     return m[::-1, ...]
 
 
-def _eye_dispatcher(N, M=None, k=None, dtype=None, order=None, *, like=None):
-    return (like,)
-
-
 @set_array_function_like_doc
 @set_module('numpy')
 def eye(N, M=None, k=0, dtype=float, order='C', *, like=None):
@@ -209,7 +205,7 @@ def eye(N, M=None, k=0, dtype=float, order='C', *, like=None):
 
     """
     if like is not None:
-        return _eye_with_like(N, M=M, k=k, dtype=dtype, order=order, like=like)
+        return _eye_with_like(like, N, M=M, k=k, dtype=dtype, order=order)
     if M is None:
         M = N
     m = zeros((N, M), dtype=dtype, order=order)
@@ -228,9 +224,7 @@ def eye(N, M=None, k=0, dtype=float, order='C', *, like=None):
     return m
 
 
-_eye_with_like = array_function_dispatch(
-    _eye_dispatcher
-)(eye)
+_eye_with_like = array_function_dispatch()(eye)
 
 
 def _diag_dispatcher(v, k=None):
@@ -369,10 +363,6 @@ def diagflat(v, k=0):
     return wrap(res)
 
 
-def _tri_dispatcher(N, M=None, k=None, dtype=None, *, like=None):
-    return (like,)
-
-
 @set_array_function_like_doc
 @set_module('numpy')
 def tri(N, M=None, k=0, dtype=float, *, like=None):
@@ -416,7 +406,7 @@ def tri(N, M=None, k=0, dtype=float, *, like=None):
 
     """
     if like is not None:
-        return _tri_with_like(N, M=M, k=k, dtype=dtype, like=like)
+        return _tri_with_like(like, N, M=M, k=k, dtype=dtype)
 
     if M is None:
         M = N
@@ -430,9 +420,7 @@ def tri(N, M=None, k=0, dtype=float, *, like=None):
     return m
 
 
-_tri_with_like = array_function_dispatch(
-    _tri_dispatcher
-)(tri)
+_tri_with_like = array_function_dispatch()(tri)
 
 
 def _trilu_dispatcher(m, k=None):