Fix the build of piglit with numpy 2.4.0 which removed newshape
and the compat glue assigning it to shape. The build fails with:
File
"/work/pobj/piglit-20250507/piglit-20250507/generated_tests/builtin_function.py",
line 296
, in column_major_values
return list(np.reshape(value, newshape=-1, order='F'))
~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: reshape() got an unexpected keyword argument 'newshape'
Fix this and a similar problem in the fp64 variant. This also
builds with in-tree py3-numpy-2.2.6p2.
Since upstream piglit pinned numpy to 1, they don't have such a fix
(and they would probably need to drop the 'shape=' part of the diffs)
Index: Makefile
===================================================================
RCS file: /cvs/ports/graphics/piglit/Makefile,v
diff -u -p -r1.27 Makefile
--- Makefile 20 May 2025 12:10:50 -0000 1.27
+++ Makefile 7 Jan 2026 14:18:50 -0000
@@ -2,7 +2,7 @@ COMMENT = automated OpenGL and OpenCL te
ONLY_FOR_ARCHS = amd64 i386
DISTNAME = piglit-20250507
-REVISION = 0
+REVISION = 1
DIST_TUPLE = fdo mesa piglit 1767af745ed96f77b16c0c205015366d1fbbdb22
${WRKDIST}/
Index: patches/patch-generated_tests_builtin_function_fp64_py
===================================================================
RCS file: patches/patch-generated_tests_builtin_function_fp64_py
diff -N patches/patch-generated_tests_builtin_function_fp64_py
--- /dev/null 1 Jan 1970 00:00:00 -0000
+++ patches/patch-generated_tests_builtin_function_fp64_py 7 Jan 2026
13:39:21 -0000
@@ -0,0 +1,26 @@
+TypeError: reshape() got an unexpected keyword argument 'newshape'
+
+The newshape parameter was deprecated in NumPy 2.1.0 and has been removed from
+numpy.reshape. Pass it positionally or use shape= on newer NumPy versions.
+
+Index: generated_tests/builtin_function_fp64.py
+--- generated_tests/builtin_function_fp64.py.orig
++++ generated_tests/builtin_function_fp64.py
+@@ -254,7 +254,7 @@ def column_major_values(value):
+ """Given a native numpy value, return a list of the scalar values
+ comprising it, in column-major order."""
+ if isinstance(value, np.ndarray):
+- return list(np.reshape(value, newshape=-1, order='F'))
++ return list(np.reshape(value, shape=-1, order='F'))
+ else:
+ return [value]
+
+@@ -262,7 +262,7 @@ def column_major_values(value):
+ def glsl_constant(value):
+ """Given a native numpy value, return GLSL code that constructs
+ it."""
+- column_major = np.reshape(np.array(value), newshape=-1, order='F')
++ column_major = np.reshape(np.array(value), shape=-1, order='F')
+ if column_major.dtype == bool:
+ values = ['true' if x else 'false' for x in column_major]
+ else:
Index: patches/patch-generated_tests_builtin_function_py
===================================================================
RCS file: patches/patch-generated_tests_builtin_function_py
diff -N patches/patch-generated_tests_builtin_function_py
--- /dev/null 1 Jan 1970 00:00:00 -0000
+++ patches/patch-generated_tests_builtin_function_py 7 Jan 2026 13:39:21
-0000
@@ -0,0 +1,26 @@
+TypeError: reshape() got an unexpected keyword argument 'newshape'
+
+The newshape parameter was deprecated in NumPy 2.1.0 and has been removed from
+numpy.reshape. Pass it positionally or use shape= on newer NumPy versions.
+
+Index: generated_tests/builtin_function.py
+--- generated_tests/builtin_function.py.orig
++++ generated_tests/builtin_function.py
+@@ -293,7 +293,7 @@ def column_major_values(value):
+ """Given a native numpy value, return a list of the scalar values
+ comprising it, in column-major order."""
+ if isinstance(value, np.ndarray):
+- return list(np.reshape(value, newshape=-1, order='F'))
++ return list(np.reshape(value, shape=-1, order='F'))
+ else:
+ return [value]
+
+@@ -301,7 +301,7 @@ def column_major_values(value):
+ def glsl_constant(value):
+ """Given a native numpy value, return GLSL code that constructs
+ it."""
+- column_major = np.reshape(np.array(value), newshape=-1, order='F')
++ column_major = np.reshape(np.array(value), shape=-1, order='F')
+ if column_major.dtype == bool:
+ values = ['true' if x else 'false' for x in column_major]
+ elif column_major.dtype == np.int64:
