codekingpro/portable-devtools
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" 5 rg)aI 5Module defining global singleton classes.6 7This module raises a RuntimeError if an attempt to reload it is made. In that8way the identities of the classes defined here are fixed and will remain so9even if numpy itself is reloaded. In particular, a function like the following10will still work correctly after numpy is reloaded::11 12 def foo(arg=np._NoValue):13 if arg is np._NoValue:14 ...15 16That was not the case when the singleton classes were defined in the numpy17``__init__.py`` file. See gh-7844 for a discussion of the reload problem that18motivated this module.19 20� N� )�21set_module�_NoValue� _CopyMode�22_is_loadedz'Reloading numpy._globals is not allowedTc �6 ^ � \ rS rSrSrSrU 4S jrS rSrU =r $ )� _NoValueType� a# Special keyword value.23 24The instance of this class may be used as the default value assigned to a25keyword if no other obvious default (e.g., `None`) is suitable,26 27Common reasons for using this keyword are:28 29- A new keyword is added to a function, and that function forwards its30 inputs to another function or method which can be defined outside of31 NumPy. For example, ``np.std(x)`` calls ``x.std``, so when a ``keepdims``32 keyword was added that could only be forwarded if the user explicitly33 specified ``keepdims``; downstream array libraries may not have added34 the same keyword, so adding ``x.std(..., keepdims=keepdims)``35 unconditionally could have broken previously working code.36- A keyword is being deprecated, and a deprecation warning must only be37 emitted when the keyword is used.38 39Nc �f >� U R ( d [ TU ] U 5 U l U R $ �N)�_NoValueType__instance�super�__new__)�cls� __class__s ��TD:\code\apps\devtools\python\user_packages\Python313\site-packages\numpy/_globals.pyr �_NoValueType.__new__5 s$ �� ��~�~� "�W�_�S� 1�C�N��~�~� � c � � g)Nz40<no value>� ��selfs r �__repr__�_NoValueType.__repr__; s � �r r )41�__name__�42__module__� __qualname__�__firstlineno__�__doc__r
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__classcell__)r s @r r r s �� ��$ �J� � � r r �numpyc �* � \ rS rSrSrSrSrSrS rSr g) r �B aZ 43An enumeration for the copy modes supported44by numpy.copy() and numpy.array(). The following three modes are supported,45 46- ALWAYS: This means that a deep copy of the input47 array will always be taken.48- IF_NEEDED: This means that a deep copy of the input49 array will be taken only if necessary.50- NEVER: This means that the deep copy will never be taken.51 If a copy cannot be avoided then a `ValueError` will be52 raised.53 54Note that the buffer-protocol could in theory do copies. NumPy currently55assumes an object exporting the buffer protocol will never do this.56TF� c �r � U [ R :X a gU [ R :X a g[ U S35 e)NTFz is neither True nor False.)r �ALWAYS�NEVER�57ValueErrorr s r �__bool__�_CopyMode.__bool__X s5 � � �9�#�#� #�� �9�?�?� "���D�6�!<�=�>�>r r N)58r r r r r r' r( � IF_NEEDEDr* r r r r r r B s � �� �F� �E��I�?r c � � \ rS rSrSS jrSrg)�_SignatureDescriptor�c Nc �\ � SSK Jn Uc [ S5 eU" U5 Ul UR $ )Nr )� _ufunc_inspect_signature_builderz:type object 'numpy.ufunc' has no attribute '__signature__')�numpy._core._internalr1 �AttributeError�
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