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Merge pull request #163 from asmeurer/release
1.8 release
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array_api_compat/__init__.py

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this implementation for the default when working with NumPy arrays.
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"""
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__version__ = '1.7.1'
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__version__ = '1.8'
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from .common import * # noqa: F401, F403

dask-xfails.txt

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# No mT on dask array
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array_api_tests/meta/test_hypothesis_helpers.py::test_symmetric_matrices
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# The test suite is incorrectly checking sums that have loss of significance
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# (https://github.com/data-apis/array-api-tests/issues/168)
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array_api_tests/test_statistical_functions.py::test_sum
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array_api_tests/test_statistical_functions.py::test_prod

docs/changelog.md

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# Changelog
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## 1.8 (2024-07-24)
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### Major Changes
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- Add support for [ndonnx](https://github.com/Quantco/ndonnx). Array API
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support itself lives in the ndonnx library, but this adds the
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{func}`~.is_ndonnx_array` helper function.
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([@adityagoel4512](https://github.com/adityagoel4512)).
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- Partial support for the [2023.12 version of the
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standard](https://data-apis.org/array-api/latest/changelog.html#v2023-12).
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This includes
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- Wrappers for `clip()`.
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- torch wrapper for `copysign()` with correct type promotion.
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Note that many of the new functions in the 2023.12 version of the standard
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are already fully implemented in upstream libraries and will already work.
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## 1.7.1 (2024-05-28)
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### Minor Changes

docs/helper-functions.rst

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.. autofunction:: is_dask_array
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.. autofunction:: is_jax_array
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.. autofunction:: is_pydata_sparse_array
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.. autofunction:: is_ndonnx_array

docs/index.md

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This is a small wrapper around common array libraries that is compatible with
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the [Array API standard](https://data-apis.org/array-api/latest/). Currently,
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NumPy, CuPy, PyTorch, Dask, JAX, and Sparse are supported. If you want support
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for other array libraries, or if you encounter any issues, please [open an
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issue](https://github.com/data-apis/array-api-compat/issues).
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NumPy, CuPy, PyTorch, Dask, JAX, ndonnx, and Sparse are supported. If you want
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support for other array libraries, or if you encounter any issues, please
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[open an issue](https://github.com/data-apis/array-api-compat/issues).
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Note that some of the functionality in this library is backwards incompatible
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with the corresponding wrapped libraries. The end-goal is to eventually make
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```
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```{note}
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There is no `array_api_compat.jax` submodule. JAX support is contained in JAX
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itself in the `jax.experimental.array_api` module. array-api-compat simply
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wraps that submodule. The main JAX support in this module consists of
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supporting it in the [helper functions](helper-functions).
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There are no `array_api_compat` submodules for JAX, sparse, or ndonnx. These
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support for these libraries is contained in the libraries themselves (JAX
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support is in the `jax.experimental.array_api` module). The
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array-api-compat support for these libraries consists of supporting them in
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the [helper functions](helper-functions).
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```
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Each will include all the functions from the normal NumPy/CuPy/PyTorch/dask.array
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You may also rename it to something else if you like (nowhere in the code
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references the name "array_api_compat").
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Alternatively, the library may be installed as dependency on PyPI.
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Alternatively, the library may be installed as dependency from PyPI.
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(scope)=
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## Scope

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