Merge pull request numba#9083 from kc611/win_32_removal

Removed windows 32 references from code and documentation
Deezy33-creator · Aug 2, 2023 · 91654d1 · 91654d1
2 parents 8fa8ddd + a29d025
commit 91654d1
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Showing 9 changed files with 21 additions and 39 deletions.
diff --git a/buildscripts/condarecipe.local/meta.yaml b/buildscripts/condarecipe.local/meta.yaml
@@ -18,7 +18,7 @@ build:
     - lib/libiomp5.dylib # [osx]
   ignore_run_exports:
     # tbb-devel triggers hard dependency on tbb, this is not the case.
-    - tbb     # [not (aarch64 or ppc64le or win32)]
+    - tbb     # [not (aarch64 or ppc64le)]
 
 requirements:
   # build and run dependencies are duplicated to avoid setuptools issues
@@ -36,9 +36,8 @@ requirements:
     # On channel https://anaconda.org/numba/
     - llvmlite >=0.41.0dev0,<0.41
     # TBB devel version is to match TBB libs.
-    # NOTE: ppc64le and aarch64 are pending testing so excluded for now, win32
-    # is not a supported parallel target.
-    - tbb-devel >=2021.6       # [not (aarch64 or ppc64le or win32)]
+    # NOTE: ppc64le and aarch64 are pending testing so excluded for now.
+    - tbb-devel >=2021.6       # [not (aarch64 or ppc64le)]
   run:
     - python >=3.8
     # NumPy 1.22.0, 1.22.1, 1.22.2 are all broken for ufuncs, see #7756
@@ -48,7 +47,7 @@ requirements:
     - llvmlite >=0.41.0dev0,<0.41
   run_constrained:
     # If TBB is present it must be at least version 2021.6
-    - tbb >=2021.6    # [not (aarch64 or ppc64le or win32)]
+    - tbb >=2021.6    # [not (aarch64 or ppc64le)]
     # avoid confusion from openblas bugs
     - libopenblas !=0.3.6      # [x86_64]
     # 0.3.17 buggy on M1 silicon
@@ -73,7 +72,7 @@ test:
     - ipython                  # [not aarch64]
     # for pycc
     - setuptools
-    - tbb >=2021.6             # [not (aarch64 or ppc64le or win32)]
+    - tbb >=2021.6             # [not (aarch64 or ppc64le)]
     - llvm-openmp              # [osx]
     # This is for driving gdb tests
     - pexpect                  # [linux64]

diff --git a/buildscripts/condarecipe.local/run_test.bat b/buildscripts/condarecipe.local/run_test.bat
@@ -3,11 +3,6 @@ set NUMBA_DISABLE_ERROR_MESSAGE_HIGHLIGHTING=1
 set NUMBA_CAPTURED_ERRORS=new_style
 set PYTHONFAULTHANDLER=1
 
-@rem no parallel target support for 32 bit windows and no TBB packages
-if "%ARCH%"=="32" (
-    set NUMBA_DISABLE_TBB=1
-)
-
 @rem Check Numba executable is there
 numba -h
 

diff --git a/docs/source/reference/envvars.rst b/docs/source/reference/envvars.rst
@@ -316,7 +316,7 @@ Compilation options
 
    If set to non-zero, enable LLVM loop vectorization.
 
-   *Default value:* 1 (except on 32-bit Windows)
+   *Default value:* 1
 
 .. envvar:: NUMBA_SLP_VECTORIZE
 

diff --git a/docs/source/reference/numpysupported.rst b/docs/source/reference/numpysupported.rst
@@ -976,16 +976,14 @@ Floating functions
  copysign            Yes          Yes
  nextafter           Yes          Yes
  modf                Yes          No
- ldexp               Yes (*)      Yes
+ ldexp               Yes          Yes
  frexp               Yes          No
  floor               Yes          Yes
  ceil                Yes          Yes
  trunc               Yes          Yes
  spacing             Yes          Yes
 ==============  =============  ===============
 
-(\*) not supported on windows 32 bit
-
 
 Datetime functions
 ------------------

diff --git a/docs/source/user/5minguide.rst b/docs/source/user/5minguide.rst
@@ -12,7 +12,7 @@ part of your code can subsequently run at native machine code speed!
 
 Out of the box Numba works with the following:
 
-* OS: Windows (32 and 64 bit), OSX, Linux (64 bit). Unofficial support on
+* OS: Windows (64 bit), OSX, Linux (64 bit). Unofficial support on
   \*BSD.
 * Architecture: x86, x86_64, ppc64le, armv8l (aarch64), M1/Arm64.
 * GPUs: Nvidia CUDA.

diff --git a/docs/source/user/installing.rst b/docs/source/user/installing.rst
@@ -12,7 +12,7 @@ Our supported platforms are:
 
 * Linux x86_64
 * Linux ppcle64 (POWER8, POWER9)
-* Windows 7 and later (32-bit and 64-bit)
+* Windows 10 and later (64-bit)
 * OS X 10.9 and later (64-bit and unofficial support on M1/Arm64)
 * \*BSD (unofficial support only)
 * NVIDIA GPUs of compute capability 5.0 and later

diff --git a/docs/upcoming_changes/9083.highlight.rst b/docs/upcoming_changes/9083.highlight.rst
@@ -0,0 +1,5 @@
+Removal of Windows 32-bit Support
+=================================
+
+This release onwards, Numba has discontinued support for Windows 32-bit
+operating systems.
diff --git a/numba/core/config.py b/numba/core/config.py
@@ -346,9 +346,7 @@ def optional_str(x):
         DUMP_OPTIMIZED = _readenv("NUMBA_DUMP_OPTIMIZED", int, DEBUG)
 
         # Force disable loop vectorize
-        # Loop vectorizer is disabled on 32-bit win32 due to a bug (#649)
-        LOOP_VECTORIZE = _readenv("NUMBA_LOOP_VECTORIZE", int,
-                                  not (IS_WIN32 and IS_32BITS))
+        LOOP_VECTORIZE = _readenv("NUMBA_LOOP_VECTORIZE", int, 1)
 
         # Enable superword-level parallelism vectorization, default is off
         # since #8705 (miscompilation).

diff --git a/numba/tests/test_function_type.py b/numba/tests/test_function_type.py
@@ -2,7 +2,7 @@
 import types as pytypes
 from numba import jit, njit, cfunc, types, int64, float64, float32, errors
 from numba import literal_unroll
-from numba.core.config import IS_32BITS, IS_WIN32
+from numba.core.config import IS_WIN32
 import ctypes
 import warnings
 
@@ -584,26 +584,13 @@ def __init__(self, fname):
                 self._name = fname
                 if fname == 'cos':
                     # test for double-precision math function
-                    if IS_WIN32 and IS_32BITS:
-                        # 32-bit Windows math library does not provide
-                        # a double-precision cos function, so
-                        # disabling the function
-                        addr = None
-                        signature = None
-                    else:
-                        addr = ctypes.cast(self.lib.cos, ctypes.c_voidp).value
-                        signature = float64(float64)
+                    addr = ctypes.cast(self.lib.cos, ctypes.c_voidp).value
+                    signature = float64(float64)
                 elif fname == 'sinf':
                     # test for single-precision math function
-                    if IS_WIN32 and IS_32BITS:
-                        # 32-bit Windows math library provides sin
-                        # (instead of sinf) that is a single-precision
-                        # sin function
-                        addr = ctypes.cast(self.lib.sin, ctypes.c_voidp).value
-                    else:
-                        # Other 32/64 bit platforms define sinf as the
-                        # single-precision sin function
-                        addr = ctypes.cast(self.lib.sinf, ctypes.c_voidp).value
+                    # Other 32/64 bit platforms define sinf as the
+                    # single-precision sin function
+                    addr = ctypes.cast(self.lib.sinf, ctypes.c_voidp).value
                     signature = float32(float32)
                 else:
                     raise NotImplementedError(