TestDataArray.test_repr FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

test_assert_allclose[Dataset] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

test_ensure_warnings_not_elevated[assert_duckarray_equal] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

test_apply_missing_dims FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

TestNamedArray.test_properties FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'__array_function__', 'imag', '__array_ufunc__', 'real'} _arrayapi - {'device', 'to_device', 'mT'}

TestNamedArray.test_expand_dims[None-3-expected_shape0-expected_dims0] FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

TestNamedArray.test_expand_dims[dim1-3-expected_shape1-expected_dims1] FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

TestNamedArray.test_expand_dims[z-3-expected_shape2-expected_dims2] FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.

test_aggregation ValueError: x must be at least 2-dimensional for matrix_transpose

test_aggregation_skipna ValueError: x must be at least 2-dimensional for matrix_transpose

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-1-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-1-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-2-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-2-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-3-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-1-3-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-2-None-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[bottleneck-2-None-False] ValueError: matrix transpose with ndim < 2 is undefined

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'real', '__array_ufunc__', 'imag', '__array_function__'} _arrayapi - {'to_device', 'mT', 'device'}

Process completed with exit code 1.

test_aggregation ValueError: x must be at least 2-dimensional for matrix_transpose

test_aggregation_skipna ValueError: x must be at least 2-dimensional for matrix_transpose

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_real_and_imag ValueError: matrix transpose with ndim < 2 is undefined

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'__array_function__', 'imag', '__array_ufunc__', 'real'} _arrayapi - {'device', 'to_device', 'mT'}

TestNamedArray.test_duck_array_class_array_api ValueError: x must be at least 2-dimensional for matrix_transpose

TestDataArrayRolling.test_rolling_reduce[bottleneck-numpy-sum-1-None-True-2] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_reduce[bottleneck-numpy-sum-1-None-False-2] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_reduce[bottleneck-numpy-sum-1-1-True-2] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_reduce[bottleneck-numpy-sum-1-1-False-2] ValueError: matrix transpose with ndim < 2 is undefined

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'imag', '__array_ufunc__', '__array_function__', 'real'} _arrayapi - {'device', 'mT', 'to_device'}

Process completed with exit code 1.

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'imag', '__array_function__', '__array_ufunc__', 'real'} _arrayapi - {'mT', 'device', 'to_device'}

Process completed with exit code 1.

test_aggregation ValueError: x must be at least 2-dimensional for matrix_transpose

test_aggregation_skipna ValueError: x must be at least 2-dimensional for matrix_transpose

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-None-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-None-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-1-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-1-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-2-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-2-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-3-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-3-False] ValueError: matrix transpose with ndim < 2 is undefined

test_aggregation ValueError: x must be at least 2-dimensional for matrix_transpose

test_aggregation_skipna ValueError: x must be at least 2-dimensional for matrix_transpose

test_ensure_warnings_not_elevated[assert_duckarray_equal] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-numpy-None-False-std] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-numpy-None-False-median] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-numpy-None-None-std] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-numpy-None-None-median] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-dask-1-True-std] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-dask-1-True-median] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestDataArrayRolling.test_rolling_wrapped_bottleneck[1-numbagg-dask-1-False-std] AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'bool_'?

TestNamedArray.test_from_array_with_explicitly_indexed assert False + where False = isinstance(array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32), CustomArrayIndexable) + where array([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.],\n [10., 11., 12., 13., 14.],\n [15.,... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32) = <xarray.NamedArray (x: 3, y: 4, z: 5)> Size: 240B\narray([[[ 0., 1., 2., 3., 4.],\n [ 5., 6., 7., 8., 9.]... [45., 46., 47., 48., 49.],\n [50., 51., 52., 53., 54.],\n [55., 56., 57., 58., 59.]]], dtype=float32).data

TestNamedArray.test_duck_array_class TypeError: a (<class 'xarray.tests.test_namedarray.CustomArrayIndexable'>) is not a valid _arrayfunction or _arrayapi. Missing following attrs: _arrayfunction - {'real', 'imag', '__array_function__', '__array_ufunc__'} _arrayapi - {'device', 'mT', 'to_device'}

Process completed with exit code 1.

test_aggregation ValueError: x must be at least 2-dimensional for matrix_transpose

test_aggregation_skipna ValueError: x must be at least 2-dimensional for matrix_transpose

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-None-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-None-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-1-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-1-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-2-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-2-False] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-3-True] ValueError: matrix transpose with ndim < 2 is undefined

TestDataArrayRolling.test_rolling_pandas_compat[numbagg-1-3-False] ValueError: matrix transpose with ndim < 2 is undefined

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Failed to save: Unable to reserve cache with key Linux-X64-py3.12-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e92b363-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, another job may be creating this cache. More details: Cache already exists. Scope: refs/pull/8344/merge, Key: Linux-X64-py3.12-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e92b363-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, Version: a2d23e1ed2659ed82c2139af6b060439ac5345ea8dad0c956f30fdd3bfee6aca

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Failed to save: Unable to reserve cache with key Linux-X64-py3.12-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e92b363-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, another job may be creating this cache. More details: Cache already exists. Scope: refs/pull/8344/merge, Key: Linux-X64-py3.12-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e92b363-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, Version: a2d23e1ed2659ed82c2139af6b060439ac5345ea8dad0c956f30fdd3bfee6aca

Failed to save: Unable to reserve cache with key Linux-X64-py3.10-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, another job may be creating this cache. More details: Cache already exists. Scope: refs/pull/8344/merge, Key: Linux-X64-py3.10-2024-11-17-873aa3ad3ac4a7fe7a151b3e2429ef07e602044eb5b3262c34b73c68c2a5d739-linux-64-xarray-tests-args-e0a578e-root-dcc80ee-bin-[object Promise]-file-7852e8e24b82f09f3fb250fb433924194a269aa60a037da5bd58a418748e3ca8, Version: a2d23e1ed2659ed82c2139af6b060439ac5345ea8dad0c956f30fdd3bfee6aca

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.

Input 'save-always' has been deprecated with message: save-always does not work as intended and will be removed in a future release. A separate `actions/cache/restore` step should be used instead. See https://github.com/actions/cache/tree/main/save#always-save-cache for more details.