1.4.1 release

CHANGELOG.md

@@ -1,3 +1,22 @@
+# 1.4.1 (2024-01-18)
+
+## Minor Changes
+
+- Add support for the upcoming NumPy 2.0 release.
+
+- Added a torch wrapper for `trace` (`torch.trace` doesn't support the
+  `offset` argument or stacking)
+
+- Wrap numpy, cupy, and torch `nonzero` to raise an error for zero-dimensional
+  input arrays.
+
+- Add torch wrapper for `newaxis`.
+
+- Improve error message for `array_namespace`
+
+- Fix linalg.cholesky returning the conjugate of the expected upper
+  decomposition for numpy and cupy.
+
 # 1.4 (2023-09-13)
 
 ## Major Changes

README.md

@@ -300,3 +300,54 @@ corresponding document does not yet exist for PyTorch, but you can examine the
 various comments in the
 [implementation](https://github.com/data-apis/array-api-compat/blob/main/array_api_compat/torch/_aliases.py)
 to see what functions and behaviors have been wrapped.
+
+
+## Releasing
+
+To release, first note that CuPy must be tested manually (it isn't tested on
+CI). Use the script
+
+```
+./test_cupy.sh
+```
+
+on a machine with a CUDA GPU.
+
+Once you are ready to release, create a PR with a release branch, so that you
+can verify that CI is passing. You must edit
+
+```
+array_api_compat/__init__.py
+```
+
+and update the version (the version is not computed from the tag because that
+would break vendorability). You should also edit
+
+```
+CHANGELOG.md
+```
+
+with the changes for the release.
+
+Then create a tag
+
+```
+git tag -a <version>
+```
+
+and push it to GitHub
+
+```
+git push origin <version>
+```
+
+Check that the `publish distributions` action works. Note that this action
+will run even if the other CI fails, so you must make sure that CI is passing
+*before* tagging.
+
+This does mean you can ignore CI failures, but ideally you should fix any
+failures or update the `*-xfails.txt` files before tagging, so that CI and the
+cupy tests pass. Otherwise it will be hard to tell what things are breaking in
+the future. It's also a good idea to remove any xpasses from those files (but
+be aware that some xfails are from flaky failures, so unless you know the
+underlying issue has been fixed, a xpass test is probably still xfail).

array_api_compat/__init__.py

@@ -17,6 +17,6 @@
 this implementation for the default when working with NumPy arrays.
 
 """
-__version__ = '1.4'
+__version__ = '1.4.1'
 
 from .common import *

array_api_compat/cupy/_aliases.py

@@ -61,8 +61,17 @@
 matmul = get_xp(cp)(_aliases.matmul)
 matrix_transpose = get_xp(cp)(_aliases.matrix_transpose)
 tensordot = get_xp(cp)(_aliases.tensordot)
-vecdot = get_xp(cp)(_aliases.vecdot)
-isdtype = get_xp(cp)(_aliases.isdtype)
+
+# These functions are completely new here. If the library already has them
+# (i.e., numpy 2.0), use the library version instead of our wrapper.
+if hasattr(cp, 'vecdot'):
+    vecdot = cp.vecdot
+else:
+    vecdot = get_xp(cp)(_aliases.vecdot)
+if hasattr(cp, 'isdtype'):
+    isdtype = cp.isdtype
+else:
+    isdtype = get_xp(cp)(_aliases.isdtype)
 
 __all__ = _aliases.__all__ + ['asarray', 'asarray_cupy', 'bool', 'acos',
                               'acosh', 'asin', 'asinh', 'atan', 'atan2',

array_api_compat/cupy/linalg.py

@@ -29,10 +29,16 @@
 pinv = get_xp(cp)(_linalg.pinv)
 matrix_norm = get_xp(cp)(_linalg.matrix_norm)
 svdvals = get_xp(cp)(_linalg.svdvals)
-vector_norm = get_xp(cp)(_linalg.vector_norm)
 diagonal = get_xp(cp)(_linalg.diagonal)
 trace = get_xp(cp)(_linalg.trace)
 
+# These functions are completely new here. If the library already has them
+# (i.e., numpy 2.0), use the library version instead of our wrapper.
+if hasattr(cp.linalg, 'vector_norm'):
+    vector_norm = cp.linalg.vector_norm
+else:
+    vector_norm = get_xp(cp)(_linalg.vector_norm)
+
 __all__ = linalg_all + _linalg.__all__
 
 del get_xp

array_api_compat/numpy/_aliases.py

@@ -61,8 +61,17 @@
 matmul = get_xp(np)(_aliases.matmul)
 matrix_transpose = get_xp(np)(_aliases.matrix_transpose)
 tensordot = get_xp(np)(_aliases.tensordot)
-vecdot = get_xp(np)(_aliases.vecdot)
-isdtype = get_xp(np)(_aliases.isdtype)
+
+# These functions are completely new here. If the library already has them
+# (i.e., numpy 2.0), use the library version instead of our wrapper.
+if hasattr(np, 'vecdot'):
+    vecdot = np.vecdot
+else:
+    vecdot = get_xp(np)(_aliases.vecdot)
+if hasattr(np, 'isdtype'):
+    isdtype = np.isdtype
+else:
+    isdtype = get_xp(np)(_aliases.isdtype)
 
 __all__ = _aliases.__all__ + ['asarray', 'asarray_numpy', 'bool', 'acos',
                               'acosh', 'asin', 'asinh', 'atan', 'atan2',

array_api_compat/numpy/linalg.py

@@ -22,10 +22,16 @@
 pinv = get_xp(np)(_linalg.pinv)
 matrix_norm = get_xp(np)(_linalg.matrix_norm)
 svdvals = get_xp(np)(_linalg.svdvals)
-vector_norm = get_xp(np)(_linalg.vector_norm)
 diagonal = get_xp(np)(_linalg.diagonal)
 trace = get_xp(np)(_linalg.trace)
 
+# These functions are completely new here. If the library already has them
+# (i.e., numpy 2.0), use the library version instead of our wrapper.
+if hasattr(np.linalg, 'vector_norm'):
+    vector_norm = np.linalg.vector_norm
+else:
+    vector_norm = get_xp(np)(_linalg.vector_norm)
+
 __all__ = linalg_all + _linalg.__all__
 
 del get_xp