DŽg.ddlZddlmZmZmZmZmZmZddlZddl m Z eje Z GddZGddZGdd eZGd d ZeZd Zd ej(defdZd ej(deeej(ffdZddeefdZdZdefdZdeefdZdedefdZdedeeeffdZd ej(defdZdZ defdZ!y)N)AnyDictOptionalProtocolTupleUnionparse_namespacec4eZdZdededej fdZy)FakeScriptObject wrapped_objscript_class_namexc.||_||_||_yN)r rreal_obj)selfr rrs j/home/mcse/projects/flask_80/flask-venv/lib/python3.12/site-packages/torch/_library/fake_class_registry.py__init__zFakeScriptObject.__init__ s&"3 N)__name__ __module__ __qualname__rstrtorch ScriptObjectrrrr r s"CCEDVDVrr c@eZdZdededeejfdZdZ y)FakeScriptMethod self_fake_obj method_nameschemac.||_||_||_yr)r r!r")rr r!r"s rrzFakeScriptMethod.__init__s +& rcPddlm}||j|jg|i|S)Nr)call_torchbind)!torch._higher_order_ops.torchbindr%r r!)rargskwargsr%s r__call__zFakeScriptMethod.__call__ s(Dd00$2B2BTTTVTTrN) rrrr rrrFunctionSchemarr)rrrrrs4'--. Urrc6eZdZedej fdZy)HasStaticMethodFromRealrcyrr)clsrs r from_realz!HasStaticMethodFromReal.from_real's rN)rrr classmethodrrr/rrrr,r,&s! !3!3  rr,cneZdZd dZdedefdZdedefdZd deddfdZ dedefdZ d d Z deddfd Z y) FakeClassRegistryreturnNci|_yr_registered_classrs rrzFakeClassRegistry.__init__-s 13r full_qualnamec||jvSrr5rr8s rhas_implzFakeClassRegistry.has_impl0s 6 666rcB|j||j|Sr)_check_registeredr6r:s rget_implzFakeClassRegistry.get_impl3s! }-%%m44rcr|j|rtjd||||j|<y)NzE%s is already registered. Previous fake class is overridden with %s.)r;logwarningr6)rr8 fake_classs rregisterzFakeClassRegistry.register7s5 == ' KKW  1;}-rc|j|stjd|y|jj |S)NziCannot deregister %s. Please use register_fake_class to register it first. Or do you dereigster it twice?)r;r@rAr6popr:s r deregisterzFakeClassRegistry.deregister@s;}}]+ KK2  ))--m< rCrFrHr=rrrr2r2,sk47c7d75c5c5;c;t;==='strr2ct|ts td|D]I}t|ts tdt|dk(rt|dtr@tdy)NzExpect flat x to be a tuple.z&Expect flat x to be a tuple of tuples.rzXExpect element of flat x to be a tuple of two elements with first element being a string) isinstancetuplerJlenr)flat_xtps r_check_valid_flat_script_objrSXse fe $9::"e$GH H2w!|:beS#9j  rrr3ct|dsy|jdvsJd|j|jdk(S)N tracing_modeF)realfakez0tracing_mode can be either real or fake but got rV)hasattrrU)rs rtracing_with_realrYfs\ 1n % >>   M :!..:J9KLM  >> v %%rc ddlmcm}ddlm}t |r|S|5|j }dddt|jtjfd|}t|j|}t||jj|}|j!D]}t#||d} | rjt%| st'd|d| dt#||} d} t)| tj*r | j,} t/||t1||| |hd} || vst2j5d|||S#1swY,xYw) Nr)_disable_current_modesc&j|Sr) from_tensor)t fake_modes rz#maybe_to_fake_obj..s)''*rzExpect z to be a callable but got .> __get_state__ __set_state____obj_flatten__z.fake object of %s doesn't implement method %s.)torch.utils._pytreeutils_pytreetorch.utils._python_dispatchr[rYrdrS tree_map_onlyrTensor"_find_fake_class_for_script_object__obj_unflatten__r _typequalified_name _method_namesgetattrcallablerJrN ScriptMethodr"setattrrr@rA) r_rpytreer[rQfake_flattenedfake_xfake_x_wrappednameattr real_attr method_schemaoverride_skip_lists ` rmaybe_to_fake_objr}qse)(C !%""$%!()) *N 0 2 D D^ TF%faggi.F.F.H!LN!WvtT* D>"WTF2LTFRS#TUU4(I=AM)U%7%78 ) 0 0  }E  "W -- LaQUV+W, K%%s E  E*rBc4dtffd }||S||S)a Register a fake implementation for this class. It's in the same spirit of registering a fake implementation for an operator but with the difference that it associates a fake class with the original torch bind class (registered with torch::class_). In this way, torch.compile can handle them properly in components such as Dynamo and AOTAutograd. This API may be used as a decorator (see example). For the fake class, users are required to provide a from_real classmethod that takes a real object and returns an instance of the fake class. All tensors in the fake object should also be properly fakified with to_fake_tensor() in from_real. Examples: # For a custom class Foo defined in test_custom_class_registration.cpp: TORCH_LIBRARY(_TorchScriptTesting, m) { m.class_("_TensorQueue") .def(torch::init()) .def("push", &TensorQueue::push) .def("pop", &TensorQueue::pop) .def("top", &TensorQueue::top) .def("size", &TensorQueue::size) .def("clone_queue", &TensorQueue::clone_queue) .def("__obj_flatten__", &TensorQueue::__obj_flatten__) .def_pickle( // __getstate__ [](const c10::intrusive_ptr& self) -> c10::Dict { return self->serialize(); }, // __setstate__ [](c10::Dict data) -> c10::intrusive_ptr { return c10::make_intrusive(std::move(data)); }); }; # We could register a fake class FakeTensorQueue in Python as follows: import torch @torch._library.register_fake_class("_TorchScriptTesting::_TensorQueue") class FakeTensorQueue: def __init__(self, queue): self.queue = queue @classmethod def __obj_unflatten__(cls, flattened_ctx): return cls(**dict(ctx)) def push(self, x): self.queue.append(x) def pop(self): return self.queue.pop(0) def size(self): return len(self.queue) In this example, the original TensorQeue need to addd a __obj_flatten__ method to the class TensorQueue and the flattend result is passed into FakeTensorQueue's __obj_unflatten__ as inputs to create a fake class. This protocol allows pytorch to look at the contents of the script object and properly handle them in the subsystems like dynamo, aot_aotugrad or more. rBcXt\}}tjj||}t |t d}|st |dt dt|jt tst t dtjt||S)Nz doesn't define a classmethod raz method is not a classmethod.) r r_C _get_custom_class_python_wrapperrp_CONVERT_FROM_REAL_NAMErJrN__dict__r0global_fake_class_registryrC_full_qual_class_name)rBnsrxtorchbind_class from_methodqualnames rinnerz"register_fake_class..inners"8,D ((CCBMj*A4H ,<=Ttjt|Sr)rrFr)rs rderegister_fake_classrs % 0 01Fx1P QQrc,tj|Sr)rr;r8s rhas_fake_classrs % . .} ==rcDt|sytj|Sr)rrr>rs rfind_fake_classr s - ( % . .} ==rrc4t|\}}d|zdz|zS)Nz__torch__.torch.classes.rar )rrrxs rrrs%x(HB % *S 04 77rr8c\|jd}t|dk(sJ|\}}}}}||fS)Nra)splitrP)r8splits_torchtorch_nsclassesr class_names r_ns_and_class_namers>   %F v;!  06-FHgr: z>rc |jj}t|\}}t|}|t d|d|d|dt d |S)Nz ScriptObject's zA haven't registered a fake class. Please use register_fake_class(z::a) to annotate a fake class for the script obj. Specifically, create a python class that implements a fake version for all the methods that're used in the program and put annotated class in the program e.g. after loading the library. The fake methods can be written in the same way as a meta kernel for an operator but need to additionally simulate the object's states. Be sure to add a z; classmethod to enable creating a fake obj from a real one.)rmrnrrrJr)rr8rrrBs rrkrks{GGI,,.M' 6NB  /J}o.//1d"ZLA?@W>WX>  ?   rrlcdt|}t|td}|st|dtdtj j j|dtj j jfd5|j|cdddS#1swYyxYw)Nz must define a classmethod z2 that converts the real object to the fake object.cSrr)ctxsrr`z%_fake_obj_from_real..?sr) rkrprrJr_library fake_impl FakeImplCtxset_ctx_getterr/)r_rrBfrom_real_methodrs @r_fake_obj_from_realr3s3A6Jz+BDI l56M5N@ B  .. " " . .y$ ?C  ! ! 0 0 ='##A&'''s B&&B/r)"loggingtypingrrrrrrrtorch._library.utilsr getLoggerrr@r rr,r2rrSrrKrYr}rrrrrrrrkrrrrrrs=>> 0g!UU" h %%P/0 &++&&4$$4 U// /04nYh7N.OYxR>T>>hsm> 8C8C8 ceCHo%*<*<". ' 'r