API: Disallow 0D input arrays in nonzero
#26268
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nonzerononzero
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Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676587056
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Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676587056
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Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676587056
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Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676587056
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Sep 20, 2024
Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676587056
copybara-service bot
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Sep 20, 2024
Create NumPy 1.x and 2.x compatible versions of np.where and np.reshape np.where: When only condition is provided, np.where(condition) is a shorthand for np.asarray(condition).nonzero(). NumPy 2.1.0rc0 disallows 0D input arrays in nonzero, so np.atleast_1d is used here to remain compatible with NumPy 1.x. See numpy/numpy#26268. np.reshape: NumPy 2.1.0rc1 added shape and copy arguments to numpy.reshape. Both newshape and shape keywords are supported (use shape as newshape will be deprecated). Besides, shape cannot be None now. To remain behavior with NumPy 1.x, we now use asarray to create an ndarray. See numpy/numpy#26292. PiperOrigin-RevId: 676957264
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Fixes #26238
This PR disallows 0D arrays input in
np.nonzeroandnp.ndarray.nonzero.