Merge pull request numba#9105 from gmarkall/numpy_1.25

NumPy 1.25 support (PR numba#9011) continued

azure-pipelines.yml

@@ -12,14 +12,14 @@ jobs:
     name: macOS
     vmImage: macos-11
     matrix:
-      py38_np121:
+      py38_np122:
         PYTHON: '3.8'
-        NUMPY: '1.21'
+        NUMPY: '1.22'
         CONDA_ENV: 'azure_ci'
         TEST_START_INDEX: 0
-      py311_np124:
+      py311_np125:
         PYTHON: '3.11'
-        NUMPY: '1.24'
+        NUMPY: '1.25'
         CONDA_ENV: 'azure_ci'
         TEST_THREADING: 'tbb'
         TEST_START_INDEX: 1
@@ -29,46 +29,35 @@ jobs:
     name: Linux
     vmImage: ubuntu-20.04
     matrix:
-      py38_np121_vanilla:
-        PYTHON: '3.8'
-        NUMPY: '1.21'
-        CONDA_ENV: azure_ci
-        VANILLA_INSTALL: yes
-        TEST_START_INDEX: 2
       py38_np122_tbb:
         PYTHON: '3.8'
         NUMPY: '1.22'
         CONDA_ENV: azure_ci
         TEST_THREADING: 'tbb'
-        TEST_START_INDEX: 3
+        TEST_START_INDEX: 2
       py38_np122_omp:
         PYTHON: '3.8'
         NUMPY: '1.22'
         CONDA_ENV: azure_ci
         TEST_THREADING: omp
-        TEST_START_INDEX: 4
+        TEST_START_INDEX: 3
       py38_np122_workqueue:
         PYTHON: '3.8'
         NUMPY: '1.22'
         CONDA_ENV: azure_ci
         TEST_THREADING: workqueue
-        TEST_START_INDEX: 5
+        TEST_START_INDEX: 4
       py38_np123_svml:
         PYTHON: '3.8'
         NUMPY: '1.23'
         CONDA_ENV: azure_ci
         TEST_SVML: yes
-        TEST_START_INDEX: 6
+        TEST_START_INDEX: 5
       py38_np124:
         PYTHON: '3.8'
         NUMPY: '1.24'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 7
-      py39_np121:
-        PYTHON: '3.9'
-        NUMPY: '1.21'
-        CONDA_ENV: azure_ci
-        TEST_START_INDEX: 8
+        TEST_START_INDEX: 6
       py39_np122_cov_doc:
         PYTHON: '3.9'
         NUMPY: '1.22'
@@ -77,47 +66,57 @@ jobs:
         RUN_FLAKE8: yes
         RUN_MYPY: yes
         BUILD_DOC: yes
-        TEST_START_INDEX: 9
+        TEST_START_INDEX: 7
       py39_np123_typeguard:
         PYTHON: '3.9'
         NUMPY: '1.23'
         CONDA_ENV: azure_ci
         RUN_TYPEGUARD: yes
-        TEST_START_INDEX: 10
+        TEST_START_INDEX: 8
       py39_np124:
         PYTHON: '3.9'
         NUMPY: '1.24'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 11
-      py310_np121:
-        PYTHON: '3.10'
-        NUMPY: '1.21'
+        TEST_START_INDEX: 9
+      py39_np125:
+        PYTHON: '3.9'
+        NUMPY: '1.25'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 12
+        TEST_START_INDEX: 10
       py310_np122:
         PYTHON: '3.10'
         NUMPY: '1.22'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 13
+        TEST_START_INDEX: 11
       py310_np123:
         PYTHON: '3.10'
         NUMPY: '1.23'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 14
+        TEST_START_INDEX: 12
       py310_np124:
         PYTHON: '3.10'
         NUMPY: '1.24'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 15
+        TEST_START_INDEX: 13
+      py310_np125:
+        PYTHON: '3.10'
+        NUMPY: '1.25'
+        CONDA_ENV: azure_ci
+        TEST_START_INDEX: 14
       py311_np123:
         PYTHON: '3.11'
         NUMPY: '1.23'
         CONDA_ENV: azure_ci
-        TEST_START_INDEX: 16
+        TEST_START_INDEX: 15
       py311_np124:
         PYTHON: '3.11'
         NUMPY: '1.24'
         CONDA_ENV: azure_ci
+        TEST_START_INDEX: 16
+      py311_np125:
+        PYTHON: '3.11'
+        NUMPY: '1.25'
+        CONDA_ENV: azure_ci
         TEST_START_INDEX: 17
 
 - template: buildscripts/azure/azure-windows.yml

buildscripts/azure/azure-windows.yml

@@ -8,14 +8,14 @@ jobs:
     vmImage: ${{ parameters.vmImage }}
   strategy:
     matrix:
-      py38_np121:
+      py38_np122:
         PYTHON: '3.8'
-        NUMPY: '1.21'
+        NUMPY: '1.22.3'
         CONDA_ENV: 'testenv'
         TEST_START_INDEX: 18
-      py311_np124:
+      py311_np125:
         PYTHON: '3.11'
-        NUMPY: '1.24'
+        NUMPY: '1.25'
         CONDA_ENV: 'testenv'
         TEST_START_INDEX: 19
 

buildscripts/condarecipe.local/meta.yaml

@@ -42,7 +42,7 @@ requirements:
   run:
     - python >=3.8
     # NumPy 1.22.0, 1.22.1, 1.22.2 are all broken for ufuncs, see #7756
-    - numpy >=1.21, !=1.22.0, !=1.22.1, !=1.22.2
+    - numpy >=1.22.3
     - importlib_metadata       # [py<39]
     # On channel https://anaconda.org/numba/
     - llvmlite >=0.41.0dev0,<0.41

buildscripts/gpuci/build.sh

@@ -35,7 +35,7 @@ fi;
 # Test with different NumPy versions with each toolkit (it's not worth testing
 # the Cartesian product of versions here, we just need to test with different
 # CUDA and NumPy versions).
-declare -A CTK_NUMPY_VMAP=( ["11.2"]="1.21" ["11.3"]="1.22" ["11.5"]="1.23" ["11.8"]="1.24")
+declare -A CTK_NUMPY_VMAP=( ["11.2"]="1.22" ["11.3"]="1.23" ["11.5"]="1.24" ["11.8"]="1.25")
 NUMPY_VER="${CTK_NUMPY_VMAP[$CUDA_TOOLKIT_VER]}"
 
 ################################################################################
@@ -51,7 +51,7 @@ nvidia-smi
 gpuci_logger "Create testing env"
 . /opt/conda/etc/profile.d/conda.sh
 gpuci_mamba_retry create -n numba_ci -y \
-                  "python=${PYTHON_VER}" \
+                  "python=3.10" \
                   "cudatoolkit=${CUDA_TOOLKIT_VER}" \
                   "rapidsai::cubinlinker" \
                   "conda-forge::ptxcompiler" \

buildscripts/incremental/setup_conda_environment.cmd

@@ -14,18 +14,14 @@ cmd /C conda info
 set CONDA_INSTALL=cmd /C conda install -q -y
 set PIP_INSTALL=pip install -q
 
-@rem Use conda-forge for NumPy 1.24 - at the time of writing it is not available
-@rem on the defaults channel.
-if %NUMPY%==1.24 (set NUMPY_CHANNEL_PKG="conda-forge::numpy") else (set NUMPY_CHANNEL_PKG="numpy")
-
 @echo on
 
 @rem Deactivate any environment
 call deactivate
 @rem Display root environment (for debugging)
 conda list
 @rem Scipy, CFFI, jinja2 and IPython are optional dependencies, but exercised in the test suite
-conda create -n %CONDA_ENV% -q -y python=%PYTHON% %NUMPY_CHANNEL_PKG%=%NUMPY% cffi pip scipy jinja2 ipython gitpython pyyaml
+conda create -n %CONDA_ENV% -q -y python=%PYTHON% numpy=%NUMPY% cffi pip scipy jinja2 ipython gitpython pyyaml
 
 call activate %CONDA_ENV%
 @rem Install latest llvmlite build

buildscripts/incremental/setup_conda_environment.sh

@@ -27,23 +27,14 @@ source deactivate
 # Display root environment (for debugging)
 conda list
 
-# Use conda-forge for NumPy 1.24 - at the time of writing it is not available
-# on the defaults channel.
-
-if [ "${NUMPY}" == "1.24" ]; then
-  NUMPY_CHANNEL_PKG=conda-forge::numpy
-else
-  NUMPY_CHANNEL_PKG=numpy
-fi
-
 # If VANILLA_INSTALL is yes, then only Python, NumPy and pip are installed, this
 # is to catch tests/code paths that require an optional package and are not
 # guarding against the possibility that it does not exist in the environment.
 # Create a base env first and then add to it...
 # NOTE: gitpython is needed for CI testing to do the test slicing
 # NOTE: pyyaml is used to ensure that the Azure CI config is valid
 
-conda create -n $CONDA_ENV -q -y ${EXTRA_CHANNELS} python=$PYTHON $NUMPY_CHANNEL_PKG=$NUMPY pip gitpython pyyaml
+conda create -n $CONDA_ENV -q -y ${EXTRA_CHANNELS} python=$PYTHON numpy=$NUMPY pip gitpython pyyaml
 
 # Activate first
 set +v

docs/source/user/installing.rst

@@ -262,6 +262,8 @@ information.
 +----------++--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
 | Numba     | Release date | Python                    | NumPy                      | llvmlite                     | LLVM              | TBB                         |
 +===========+==============+===========================+============================+==============================+===================+=============================+
+| 0.58.0    | UNRELEASED   | 3.8.x <= version < 3.12   | 1.21 <= version < 1.26     | 0.41.x                       | 14.x              | 2021.6 <= version           |
++-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
 | 0.57.1    | 2023-06-21   | 3.8.x <= version < 3.12   | 1.21 <= version < 1.25     | 0.40.x                       | 14.x              | 2021.6 <= version           |
 +-----------+--------------+---------------------------+----------------------------+------------------------------+-------------------+-----------------------------+
 | 0.57.0    | 2023-05-01   | 3.8.x <= version < 3.12   | 1.21 <= version < 1.25     | 0.40.x                       | 14.x              | 2021.6 <= version           |

docs/upcoming_changes/9011.np_support.rst

@@ -0,0 +1,5 @@
+
+Add support for NumPy 1.25
+==========================
+
+Extend Numba to support new and changed features released in NumPy 1.25.

numba/core/typing/npdatetime.py

@@ -11,6 +11,7 @@
                                          AbstractTemplate, infer_global, infer,
                                          infer_getattr, signature)
 from numba.np import npdatetime_helpers
+from numba.np.numpy_support import numpy_version
 
 
 # timedelta64-only operations
@@ -144,13 +145,22 @@ class TimedeltaTrueDiv(TimedeltaDivOp):
 class TimedeltaFloorDiv(TimedeltaDivOp):
     key = operator.floordiv
 
-@infer_global(operator.eq)
-class TimedeltaCmpEq(TimedeltaCmpOp):
-    key = operator.eq
+if numpy_version >= (1, 25):
+    @infer_global(operator.eq)
+    class TimedeltaCmpEq(TimedeltaOrderedCmpOp):
+        key = operator.eq
 
-@infer_global(operator.ne)
-class TimedeltaCmpNe(TimedeltaCmpOp):
-    key = operator.ne
+    @infer_global(operator.ne)
+    class TimedeltaCmpNe(TimedeltaOrderedCmpOp):
+        key = operator.ne
+else:
+    @infer_global(operator.eq)
+    class TimedeltaCmpEq(TimedeltaCmpOp):
+        key = operator.eq
+
+    @infer_global(operator.ne)
+    class TimedeltaCmpNe(TimedeltaCmpOp):
+        key = operator.ne
 
 @infer_global(operator.lt)
 class TimedeltaCmpLt(TimedeltaOrderedCmpOp):
@@ -228,7 +238,6 @@ def generic(self, args, kws):
         left, right = args
         if isinstance(left, types.NPDatetime) and isinstance(right,
                                                              types.NPDatetime):
-            # All units compatible...
             unit = npdatetime_helpers.get_best_unit(left.unit, right.unit)
             return signature(types.NPTimedelta(unit), left, right)
 

numba/cpython/numbers.py

@@ -361,6 +361,38 @@ def int_ne_impl(context, builder, sig, args):
     return impl_ret_untracked(context, builder, sig.return_type, res)
 
 
+def int_signed_unsigned_cmp(op):
+    def impl(context, builder, sig, args):
+        (left, right) = args
+        # This code is translated from the NumPy source.
+        # What we're going to do is divide the range of a signed value at zero.
+        # If the signed value is less than zero, then we can treat zero as the
+        # unsigned value since the unsigned value is necessarily zero or larger
+        # and any signed comparison between a negative value and zero/infinity
+        # will yield the same result. If the signed value is greater than or
+        # equal to zero, then we can safely cast it to an unsigned value and do
+        # the expected unsigned-unsigned comparison operation.
+        # Original: https://github.com/numpy/numpy/pull/23713
+        cmp_zero = builder.icmp_signed('<', left, Constant(left.type, 0))
+        lt_zero = builder.icmp_signed(op, left, Constant(left.type, 0))
+        ge_zero = builder.icmp_unsigned(op, left, right)
+        res = builder.select(cmp_zero, lt_zero, ge_zero)
+        return impl_ret_untracked(context, builder, sig.return_type, res)
+    return impl
+
+
+def int_unsigned_signed_cmp(op):
+    def impl(context, builder, sig, args):
+        (left, right) = args
+        # See the function `int_signed_unsigned_cmp` for implementation notes.
+        cmp_zero = builder.icmp_signed('<', right, Constant(right.type, 0))
+        lt_zero = builder.icmp_signed(op, Constant(right.type, 0), right)
+        ge_zero = builder.icmp_unsigned(op, left, right)
+        res = builder.select(cmp_zero, lt_zero, ge_zero)
+        return impl_ret_untracked(context, builder, sig.return_type, res)
+    return impl
+
+
 def int_abs_impl(context, builder, sig, args):
     [x] = args
     ZERO = Constant(x.type, None)

numba/cuda/tests/cudapy/test_gufunc.py

@@ -1,5 +1,4 @@
 import numpy as np
-import numpy.core.umath_tests as ut
 
 from collections import namedtuple
 from numba import void, int32, float32, float64
@@ -42,7 +41,7 @@ def test_gufunc_small(self):
                                                                    5)
 
         C = gufunc(A, B)
-        Gold = ut.matrix_multiply(A, B)
+        Gold = np.matmul(A, B)
         self.assertTrue(np.allclose(C, Gold))
 
     def test_gufunc_auto_transfer(self):
@@ -58,7 +57,7 @@ def test_gufunc_auto_transfer(self):
         dB = cuda.to_device(B)
 
         C = gufunc(A, dB).copy_to_host()
-        Gold = ut.matrix_multiply(A, B)
+        Gold = np.matmul(A, B)
         self.assertTrue(np.allclose(C, Gold))
 
     def test_gufunc(self):
@@ -72,7 +71,7 @@ def test_gufunc(self):
                                                                    5)
 
         C = gufunc(A, B)
-        Gold = ut.matrix_multiply(A, B)
+        Gold = np.matmul(A, B)
         self.assertTrue(np.allclose(C, Gold))
 
     def test_gufunc_hidim(self):
@@ -84,7 +83,7 @@ def test_gufunc_hidim(self):
         B = np.arange(matrix_ct * 4 * 5, dtype=np.float32).reshape(4, 25, 4, 5)
 
         C = gufunc(A, B)
-        Gold = ut.matrix_multiply(A, B)
+        Gold = np.matmul(A, B)
         self.assertTrue(np.allclose(C, Gold))
 
     def test_gufunc_new_axis(self):
@@ -94,7 +93,7 @@ def test_gufunc_new_axis(self):
         X = np.random.randn(10, 3, 3)
         Y = np.random.randn(3, 3)
 
-        gold = ut.matrix_multiply(X, Y)
+        gold = np.matmul(X, Y)
 
         res1 = gufunc(X, Y)
         np.testing.assert_allclose(gold, res1)
@@ -122,7 +121,7 @@ def test_gufunc_stream(self):
         C = dC.copy_to_host(stream=stream)
         stream.synchronize()
 
-        Gold = ut.matrix_multiply(A, B)
+        Gold = np.matmul(A, B)
 
         self.assertTrue(np.allclose(C, Gold))