U ʹj@sUddlmZddlmZddlZddlZddlZddddgZeZ ee e d <d gZ d dZ Gd ddZd dZdddZdddZdS)) OpOverload)SetNLibraryimpldefinefallthrough_kernel_implsZprimcCs tddS)zZ A dummy function to pass to ``Library.impl`` in order to register a fallthrough. z,fallthrough_kernel() should never be called.N)NotImplementedErrorr r L/var/www/html/bwave/python/venv/lib/python3.8/site-packages/torch/library.pyrsc@s6eZdZdZd ddZddZd ddZdd d Zd S)raC A class to create libraries that can be used to register new operators or override operators in existing libraries from Python. A user can optionally pass in a dispatch keyname if they only want to register kernels corresponding to only one specific dispatch key. To create a library to override operators in an existing library (with name ns), set the kind to "IMPL". To create a new library (with name ns) to register new operators, set the kind to "DEF". To create a fragment of a possibly existing library to register operators (and bypass the limitation that there is only one library for a given namespace), set the kind to "FRAGMENT". Args: ns: library name kind: "DEF", "IMPL" (default: "IMPL"), "FRAGMENT" dispatch_key: PyTorch dispatch key (default: "") cCs|dkrtd||tkr4|dks*|dkr4t|dtjddd}|j|j}}tj||||||_ ||_ t |_ ||_ ||_t|tt|j dS) N)ZIMPLDEFFRAGMENTzUnsupported kind: rrzJ is a reserved namespace. Please try creating a library with another name.)limitr) ValueError_reserved_namespaces traceback extract_stackfilenamelinenotorch_CZ_dispatch_librarymnsset _op_implskind dispatch_keyweakreffinalize _del_libraryr )selfrrrframerrr r r __init__*s  zLibrary.__init__cCsd|jd|jd|jdS)Nz Library(kind=z, ns=z, dispatch_key=z)>)rrr)r#r r r __repr__>szLibrary.__repr__cCs$|dkrtd||j||S)azDefines a new operator and its semantics in the ns namespace. Args: schema: function schema to define a new operator. alias_analysis (optional): Indicates if the aliasing properties of the operator arguments can be inferred from the schema (default behavior) or not ("CONSERVATIVE"). Returns: name of the operator as inferred from the schema. Example:: >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LIBRARY) >>> my_lib = Library("foo", "DEF") >>> my_lib.define("sum(Tensor self) -> Tensor") )r Z FROM_SCHEMAZ CONSERVATIVEzInvalid alias_analysis type ) RuntimeErrorrr)r#schemaalias_analysisr r r rAszLibrary.definecCs0t|stdt||dkr(|j}t|tr8|}n8t|trh|jj}|jj }|dkrp|d|}nt d|j d| ddd|}|t krt d| dd||j |d kr|}d|kr|j d|}tj|d rt d |d |j||dkr|nd |t ||j|d S)aRegisters the function implementation for an operator defined in the library. Args: op_name: operator name (along with the overload) or OpOverload object. fn: function that's the operator implementation for the input dispatch key or :func:`~fallthrough_kernel` to register a fallthrough. dispatch_key: dispatch key that the input function should be registered for. By default, it uses the dispatch key that the library was created with. Example:: >>> my_lib = Library("aten", "IMPL") >>> def div_cpu(self, other): >>> return self * (1 / other) >>> my_lib.impl("div.Tensor", div_cpu, "CPU") z;Input function is required to be a callable but found type r .zQimpl should be passed either a name or an OpOverload object as the first argument/z::zThis is not allowed since there's already a kernel registered from python overriding {}'s behavior for {} dispatch key and {} namespace.ZMetaZCompositeImplicitAutogradz?We should not register a meta kernel directly to the operator 'z', because it has a CompositeImplicitAutograd kernel in core. Instead we should let the operator decompose, and ensure that we have meta kernels for the base ops that it decomposes into.N)callable TypeErrortyper isinstancestrrZ_schemaname overload_namer'rsplitr formatrrZ%_dispatch_has_kernel_for_dispatch_keyrraddr)r#Zop_namefnrr2r3keyZdispatcher_op_namer r r rVs<      z Library.implN)r )r )r )__name__ __module__ __qualname____doc__r%r&rrr r r r rs   cCs ||8}dSNr )Zcaptured_implsZop_implsr r r r"sr"r csfdd}|S)Ncs||Sr=)r)frlibr2r r wrapszimpl..wrapr )r@r2rrAr r?r rscsfdd}|S)Ncs}|||Sr=)rr)r>r2r)r@r(r r rAs  zdefine..wrapr )r@r(r)rAr rBr rs)r )r )Z_opsrtypingrrrr __all__rr r1__annotations__rrrr"rrr r r r s   {