test newer dask

Author: lithomas1

.github/workflows/array-api-tests-numpy-1-26.yml

@@ -0,0 +1,11 @@
+name: Array API Tests (NumPy 1.26)
+
+on: [push, pull_request]
+
+jobs:
+  array-api-tests-numpy-latest:
+    uses: ./.github/workflows/array-api-tests.yml
+    with:
+      package-name: numpy
+      package-version: '== 1.26.*'
+      xfails-file-extra: '-1-26'

.github/workflows/array-api-tests-numpy.yml renamed to .github/workflows/array-api-tests-numpy-latest.yml

@@ -10,3 +10,5 @@ jobs:
       # Proper linalg testing will require
       # https://github.com/data-apis/array-api-tests/pull/101
       pytest-extra-args: "--disable-extension linalg"
+      extra-env-vars: |
+        ARRAY_API_TESTS_SKIP_DTYPES=uint16,uint32,uint64

.github/workflows/array-api-tests-torch.yml

@@ -27,7 +27,10 @@ on:
       skips-file-extra:
         required: false
         type: string
-
+      extra-env-vars:
+        required: false
+        type: string
+        description: "Multiline string of environment variables to set for the test run."
 
 env:
   PYTEST_ARGS: "--max-examples 200 -v -rxXfE --ci ${{ inputs.pytest-extra-args }} --hypothesis-disable-deadline"
@@ -54,6 +57,11 @@ jobs:
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+    - name: Set Extra Environment Variables
+      # Set additional environment variables if provided
+      if: inputs.extra-env-vars
+      run: |
+        echo "${{ inputs.extra-env-vars }}" >> $GITHUB_ENV
     - name: Install dependencies
       # NumPy 1.21 doesn't support Python 3.11. There doesn't seem to be a way
       # to put this in the numpy 1.21 config file.

.github/workflows/array-api-tests.yml

@@ -13,7 +13,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Download Artifact
-        uses: dawidd6/action-download-artifact@v3
+        uses: dawidd6/action-download-artifact@v6
         with:
           workflow: docs-build.yml
           name: docs-build

.github/workflows/docs-deploy.yml

@@ -94,7 +94,7 @@ jobs:
       if: >-
         (github.event_name == 'push' && startsWith(github.ref, 'refs/tags'))
         || (github.event_name == 'workflow_dispatch' && github.event.inputs.publish == 'true')
-      uses: pypa/gh-action-pypi-publish@v1.8.14
+      uses: pypa/gh-action-pypi-publish@v1.9.0
       with:
         repository-url: https://test.pypi.org/legacy/
         print-hash: true
@@ -107,6 +107,6 @@ jobs:
 
     - name: Publish distribution 📦 to PyPI
       if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags')
-      uses: pypa/gh-action-pypi-publish@v1.8.14
+      uses: pypa/gh-action-pypi-publish@v1.9.0
       with:
         print-hash: true

.github/workflows/publish-package.yml

@@ -6,7 +6,7 @@ jobs:
     strategy:
       matrix:
         python-version: ['3.9', '3.10', '3.11', '3.12']
-        numpy-version: ['1.21', '1.26', 'dev']
+        numpy-version: ['1.21', '1.26', '2.0', 'dev']
         exclude:
           - python-version: '3.11'
             numpy-version: '1.21'
@@ -28,6 +28,11 @@ jobs:
           else
             PIP_EXTRA='numpy==1.26.*'
           fi
+
+          if [ "${{ matrix.python-version }}" == "3.9" ]; then
+            sed -i '/^ndonnx/d' requirements-dev.txt
+          fi
+
           python -m pip install -r requirements-dev.txt $PIP_EXTRA
 
       - name: Run Tests

.github/workflows/tests.yml

@@ -2,8 +2,8 @@
 
 This is a small wrapper around common array libraries that is compatible with
 the [Array API standard](https://data-apis.org/array-api/latest/). Currently,
-NumPy, CuPy, PyTorch, Dask, JAX and `sparse` are supported. If you want support
-for other array libraries, or if you encounter any issues, please [open an
-issue](https://github.com/data-apis/array-api-compat/issues).
+NumPy, CuPy, PyTorch, Dask, JAX, ndonnx and `sparse` are supported. If you want
+support for other array libraries, or if you encounter any issues, please [open
+an issue](https://github.com/data-apis/array-api-compat/issues).
 
 See the documentation for more details https://data-apis.org/array-api-compat/

README.md

@@ -17,6 +17,6 @@
 this implementation for the default when working with NumPy arrays.
 
 """
-__version__ = '1.6'
+__version__ = '1.8'
 
 from .common import *  # noqa: F401, F403

array_api_compat/__init__.py

@@ -12,7 +12,7 @@
 from typing import NamedTuple
 import inspect
 
-from ._helpers import _check_device
+from ._helpers import array_namespace, _check_device
 
 # These functions are modified from the NumPy versions.
 
@@ -264,6 +264,66 @@ def var(
 ) -> ndarray:
     return xp.var(x, axis=axis, ddof=correction, keepdims=keepdims, **kwargs)
 
+
+# The min and max argument names in clip are different and not optional in numpy, and type
+# promotion behavior is different.
+def clip(
+    x: ndarray,
+    /,
+    min: Optional[Union[int, float, ndarray]] = None,
+    max: Optional[Union[int, float, ndarray]] = None,
+    *,
+    xp,
+    # TODO: np.clip has other ufunc kwargs
+    out: Optional[ndarray] = None,
+) -> ndarray:
+    def _isscalar(a):
+        return isinstance(a, (int, float, type(None)))
+    min_shape = () if _isscalar(min) else min.shape
+    max_shape = () if _isscalar(max) else max.shape
+    result_shape = xp.broadcast_shapes(x.shape, min_shape, max_shape)
+
+    wrapped_xp = array_namespace(x)
+
+    # np.clip does type promotion but the array API clip requires that the
+    # output have the same dtype as x. We do this instead of just downcasting
+    # the result of xp.clip() to handle some corner cases better (e.g.,
+    # avoiding uint64 -> float64 promotion).
+
+    # Note: cases where min or max overflow (integer) or round (float) in the
+    # wrong direction when downcasting to x.dtype are unspecified. This code
+    # just does whatever NumPy does when it downcasts in the assignment, but
+    # other behavior could be preferred, especially for integers. For example,
+    # this code produces:
+
+    # >>> clip(asarray(0, dtype=int8), asarray(128, dtype=int16), None)
+    # -128
+
+    # but an answer of 0 might be preferred. See
+    # https://github.com/numpy/numpy/issues/24976 for more discussion on this issue.
+
+
+    # At least handle the case of Python integers correctly (see
+    # https://github.com/numpy/numpy/pull/26892).
+    if type(min) is int and min <= xp.iinfo(x.dtype).min:
+        min = None
+    if type(max) is int and max >= xp.iinfo(x.dtype).max:
+        max = None
+
+    if out is None:
+        out = wrapped_xp.asarray(xp.broadcast_to(x, result_shape), copy=True)
+    if min is not None:
+        a = xp.broadcast_to(xp.asarray(min), result_shape)
+        ia = (out < a) | xp.isnan(a)
+        # torch requires an explicit cast here
+        out[ia] = wrapped_xp.astype(a[ia], out.dtype)
+    if max is not None:
+        b = xp.broadcast_to(xp.asarray(max), result_shape)
+        ib = (out > b) | xp.isnan(b)
+        out[ib] = wrapped_xp.astype(b[ib], out.dtype)
+    # Return a scalar for 0-D
+    return out[()]
+
 # Unlike transpose(), the axes argument to permute_dims() is required.
 def permute_dims(x: ndarray, /, axes: Tuple[int, ...], xp) -> ndarray:
     return xp.transpose(x, axes)
@@ -465,6 +525,6 @@ def isdtype(
            'linspace', 'ones', 'ones_like', 'zeros', 'zeros_like',
            'UniqueAllResult', 'UniqueCountsResult', 'UniqueInverseResult',
            'unique_all', 'unique_counts', 'unique_inverse', 'unique_values',
-           'astype', 'std', 'var', 'permute_dims', 'reshape', 'argsort',
+           'astype', 'std', 'var', 'clip', 'permute_dims', 'reshape', 'argsort',
            'sort', 'nonzero', 'sum', 'prod', 'ceil', 'floor', 'trunc',
            'matmul', 'matrix_transpose', 'tensordot', 'vecdot', 'isdtype']