o 8ήc@sddlZddlmZddlmZmZddlmZddlmZddlm Z Gddde Z Gd d d e Z Gd d d e Z dddZddZdS)N) _internal)ParallelUFuncBuilderParallelGUFuncBuilder)DelayedRegistry)dufunc)gufuncc@s0eZdZeddZeddZeddZdS)_BaseVectorizecCs |ddS)Nidentitypopclskwargsr@/tmp/pip-target-vg8gfxp4/lib/python/numba/np/ufunc/decorators.py get_identity  z_BaseVectorize.get_identitycCs |ddS)NcacheFr r rrr get_cacherz_BaseVectorize.get_cachecCs4|dd}z|j|WStytd|w)NtargetcpuzUnsupported target: %s)r target_registryKeyError ValueError)r rrrrrget_target_implementations    z(_BaseVectorize.get_target_implementationN)__name__ __module__ __qualname__ classmethodrrrrrrrr s  rc@$eZdZeejedZddZdS) VectorizerparallelcKs.||}||}||}|||||dS)Nr r targetoptions)rrr)r funckwsr rimprrr__new__"s   zVectorize.__new__N) rrrrrDUFuncrrr(rrrrr   r c@r) GUVectorizer!cKsZ||}||}||}|tjur$|dd}|||||||dS||||||dS)N is_dynamicF)r rr,r$r#)rrrrGUFuncr )r r% signaturer&r rr'is_dynrrrr(-s       zGUVectorize.__new__N) rrrrrr-rrr(rrrrr+)r*r+rc sLt|tr |gnt|rtj|fiS|dur|fdd}|S)avectorize(ftylist_or_function=(), target='cpu', identity=None, **kws) A decorator that creates a Numpy ufunc object using Numba compiled code. When no arguments or only keyword arguments are given, vectorize will return a Numba dynamic ufunc (DUFunc) object, where compilation/specialization may occur at call-time. Args ----- ftylist_or_function: function or iterable When the first argument is a function, signatures are dealt with at call-time. When the first argument is an iterable of type signatures, which are either function type object or a string describing the function type, signatures are finalized at decoration time. Keyword Args ------------ target: str A string for code generation target. Default to "cpu". identity: int, str, or None The identity (or unit) value for the element-wise function being implemented. Allowed values are None (the default), 0, 1, and "reorderable". cache: bool Turns on caching. Returns -------- A NumPy universal function Examples ------- @vectorize(['float32(float32, float32)', 'float64(float64, float64)'], identity=1) def sum(a, b): return a + b @vectorize def sum(a, b): return a + b @vectorize(identity=1) def mul(a, b): return a * b Ncs@t|fi}D]}||q tdkr||SNr)r addlendisable_compile build_ufunc)r%vecsigftylistr&rrwrapzs   zvectorize..wrap) isinstancestrinspect isfunctionrr))ftylist_or_functionr&r9rr7r vectorize:s 8 r?cspt|dkrg|dddnt|dkr"|d|dntdttr.gfdd}|S) aguvectorize(ftylist, signature, target='cpu', identity=None, **kws) A decorator to create numpy generialized-ufunc object from Numba compiled code. Args ----- ftylist: iterable An iterable of type signatures, which are either function type object or a string describing the function type. signature: str A NumPy generialized-ufunc signature. e.g. "(m, n), (n, p)->(m, p)" identity: int, str, or None The identity (or unit) value for the element-wise function being implemented. Allowed values are None (the default), 0, 1, and "reorderable". cache: bool Turns on caching. target: str A string for code generation target. Defaults to "cpu". Returns -------- A NumPy generialized universal-function Example ------- @guvectorize(['void(int32[:,:], int32[:,:], int32[:,:])', 'void(float32[:,:], float32[:,:], float32[:,:])'], '(x, y),(x, y)->(x, y)') def add_2d_array(a, b, c): for i in range(c.shape[0]): for j in range(c.shape[1]): c[i, j] = a[i, j] + b[i, j] rr,Tz3guvectorize() takes one or two positional argumentscsBt|fi}D]}||q tdkr||Sr0)r+r1r2r3r4)r%guvecftyr8rr.rrr9s   zguvectorize..wrap)r2 setdefault TypeErrorr:r;)argsrr9rrDr guvectorizes ,   rH)r)r<numba.np.ufuncrnumba.np.ufunc.parallelrrnumba.core.registryrrrobjectrr r+r?rHrrrrs      K