jUdZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl Z ddl Z ddl Z ddl Z ddlZddlZddl mZmZmZmZmZmZmZmZmZmZmZmZddlZddlZddlmcm Z!ddl"m#Z#ddl$m#Z%m&Z'ddl(m)Z)m*Z*m+Z+ddl,m&Z&e j-dkZ.ee/e0d <e j-d kZ1ee/e0d <eeeed ffe0d <e j-d kre j2Z3ndZ3ee0d< ddl4Z4e4j5Z5n#e6$rddl7Z7e7j5Z5YnwxYwej8Z9de0d<dZ:de/fdZ;GddZ<e<Z=e>ddD]Z?e=e@de?<de/fdZAdgdeBfdZCGddZDeDZEdZFdhd eGfd!ZHd"ZId#ZJde/fd$ZKdeeBfd%ZLd&ZMd'ZNd(ZOd)ZPGd*d+ZQd,ZRd-ZSGd.d/ejTZUdid1ZVd2ZWd3ZXd4ZYde/fd5ZZde/fd6Z[de/fd7Z\de/fd8Z]d9Z^d:Z_djd;Z`iaaeeBeefe0d<<d=Zbd>Zcd?Zdd@ZedAZfdjdBZgdeeBeGffdCZhiaieeBeeBeeffe0dD<iZjeeeBeBfeGfe0dE<dFZkdGZlde/fdHZmde/fdIZnde/fdJZodKZpdLZqde/fdMZrde/fdNZsejtjuvrddOlwmxZxddPlmyZyde/fdQZzde/fdRZ{nde/fdSZ{dTZ| dkdUeej}j~jfdVZdWeBdXeeBdYeed ffdZZejd[Zdjd\Zde/fd]Zdjd^Zdjd_Zdjd`Zde/fdaZde/fdbZGdcddejZdeZdeeBfdfZe j-d krVeWejjeWejjeWejjeWejjdSdS)lz The weak_script annotation needs to be here instead of inside torch/jit/ so it can be used in other places in torch/ (namely torch.nn) without running into circular dependency problems N) AnyCallableDictFinal ForwardRefget_args get_originListOptionalTupleTypeUnion)_Await)rFuture) fake_rangeget_source_lines_and_file parse_def)r) IS_PY39_PLUSr IS_PY310_PLUS.BuiltinUnionTypeLockTypez8weakref.WeakKeyDictionary[Callable, Dict[str, Callable]]boolean_dispatched__torch_jit_dataclassreturnct|do@|jdvo7t|tup!t |t tS)N __module__>typingtyping_extensions)hasattrr!r r isinstancetypeanns DC:\Projects\Historical\venv\Lib\site-packages\torch/_jit_internal.pyis_finalr*RsN\"" G N= = G __ % ECe)E)EceZdZdZdS)BroadcastingListClscdSNr)selftypess r) __getitem__zBroadcastingListCls.__getitem__\sr+N)__name__r! __qualname__r2rr+r)r-r-[s#r+r-BroadcastingListcdS)a Function that returns True when in compilation and False otherwise. 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(t ( ( (   ";//4!))#s33 !))#s33 5 * $ $%KK'4K d{{ 2t 2 2 2 2 2    t ##r+c eZdZdZdZdZdS) SourceLoaderci|_dSr/contentr0s r)__init__zSourceLoader.__init__s  r+c||j|<dSr/rV)r0fnsources r)cachezSourceLoader.caches! Rr+c6|j|Sr/)rWget)r0r[s r) get_sourcezSourceLoader.get_sources|###r+N)r3r!r4rYr]r`rr+r)rTrTsA"""$$$$$r+rTcjfddtttfffd fdfdS)a_ Creates a resolution callback that will look up qualified names in an environment, starting with `lookup_base` for the base of any qualified names, then proceeding down the lookup chain with the resolved object. 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For example, the following program prints 2:: def bar(): cb = createResolutionCallbackFromFrame(1) print(cb("foo")) def baz(): foo = 2 bar() baz() rrcNceZdZfdZdS).createResolutionCallbackFromFrame..envc|vr|S|vr|S|ttvrtt|SdSr/)dirbuiltinsrG)r0key f_globalsf_localss r) __getattr__z:createResolutionCallbackFromFrame..env.__getattr__<sTh}$ !! ~%H %%x---&%r+Nr3r!r4r)rrsr)envr;s3 . . . . . . . .r+r)inspect currentframef_backrrr)rframertrrrs @@r)!createResolutionCallbackFromFramers:  " "E A i!m       Q i!m      ~HI........... +3355 1 11r+ci}||jt|jjD]\}}|j|j||<|S)zC Get a dictionary of closed over variables from a function )update __globals__ enumerate__code__ co_freevars __closure__ cell_contents)r[capturesindex captured_names r) get_closurerGs\H OOBN### )"+*A B BFF}"$."7"E Or+cnt|Gfdd}t|S)z Create a resolutionCallback by introspecting the function instead of looking up the stack for the enclosing scope ceZdZfdZdS);createResolutionCallbackFromClosure..closure_lookupc|vr|Stt|rtt|Stt|rtt|SdSr/)r$r"rGr)r0rclosures r)rzGcreateResolutionCallbackFromClosure..closure_lookup.__getattr__s_g~~s|#%% .vs+++3'' .x---4r+Nr)rsr)closure_lookuprs.       r+r)rr)r[rrs @r)#createResolutionCallbackFromClosurersZ "ooG           +>>+;+; < <z%can_compile_class..sP      WS$55 6 6 T   r+c.g|]}t|dS)r)r$rr[s r)rz%can_compile_class..s"666BJ''666r+) is_ignored_fnrCnnModulerrlistrz issubclass__dict__all)rignored_builtin_classesnamesfnshas_codes` r)can_compile_classrsSu %xtYG#.//u LE       C 76#666H x==r+c tj|}n#t$rgcYSwxYwg}|jD]+\}}|j|jks||,|S)aU Gets names of all POSITIONAL_OR_KEYWORD arguments for callable `fn`. 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Returns: Argument names: List[str] )r signaturerz parametersitemskindPOSITIONAL_OR_KEYWORDrq)r[callable_signatureargument_namesrJparams r)get_callable_argument_namesrs$.r22  N)4::<<$$ ezU888 d#### s  &&cNt|tjr|jSt|tjr.dt |j|jgSt|tj rAtr|j n |j j}t |jdt |dSt|tj r$dd|j DSt|tjr|jSdS)z Convert an AST node containing a type annotation to the string present in the source that represents the same annotation. rBrmrnrlc,g|]}t|Sr)get_annotation_str)relts r)rz&get_annotation_str..s!LLLS+C00LLLr+N)r%astNameid Attributejoinrr{attr Subscriptrslicer eltsConstant) annotationsubscript_slices r)rrs *ch'' %} J . . %xx+J,<==zOPPP J . .%.:V*** @P@V$Z%566__9KO9\9\____ J * *%xxLLJOLLLMMM J - -%"$$ 4r+cZt|}|< tj|}n&#t$r}t d|d|d}~wwxYwtj|}d|jD}tj tj |}t|j dks%t|j dtjst!d|d|j d}i}|jjD]8}|jrt'|jnd} | "|j} | |vr || || <9t'|j} | du} |j} | tjjuot| t2 }| r|r| || <|S) a Get a dictionary containing type resolution mappings necessary to resolve types for the literal annotations on 'fn'. These are not considered to be closed-over by fn and must be obtained separately (e.g. using this function). Args: fn: A callable. Returns: A Dict[str, Any] containing a mapping from the literal annotations used on fn to the Python objects they refer to. NzFailed to get source for z using inspect.getsourceci|]?\}}|jtjjut |jt 7||j@Sr)rr Parameteremptyr%str)rrJ parameters r) z*get_type_hint_captures..sT D)  w'8'> > >9/55 ? i" > > >r+rcrz Expected z to be a function)loaderr`r getsourceOSErrorrrrrparsetextwrapdedentrobodyr% FunctionDefrKargsrrargreturnsreturn_annotationrrr)r[srcer name_to_typeafannotation_to_typerarg_annotation_strarg_nameliteral_return_annotationvalid_literal_annotationrvalid_return_annotation_types r)get_type_hint_capturesrs   B  C { #B''CC   HBHHH  !"%%I(399;;L (/#&&''A 16{{az!&)S_EE.?sN      WS$// 0 0 T   r+cZg|](}tj|t|d&|)S)r)r isbuiltinr$rs r)rz;createResolutionCallbackForClassMethods..Gs7 X X X"7#4R#8#8 XWR=W=W X2 X X Xr+cH|vr|Stt|dSr/)rGr)rrs r)lookup_in_classz@createResolutionCallbackForClassMethods..lookup_in_classNs( (??C= 8S$// /r+)rrrr)rrr[rrs` @r)'createResolutionCallbackForClassMethodsr8s    L   C Y X X X XCH44 B(((.r22333300000 r+c(fd}jjj}|_n=jjj}|_n j jd}ntd||_|||_|||_dt|<|S)z Dispatches to either of 2 script functions based on a boolean argument. In TorchScript, the boolean argument must be constant so that the correct function to use can be determined at compile time. c|}|vr |}nt|kr|}|r|i|S|i|Sr/)ro)rkwargs dispatch_flag arg_indexrdefaultif_falseif_trues r)r[zboolean_dispatch..fnfsk v  "8,MM T " " OM  -7D+F++ +8T,V,, ,r+Nz&only one function can have a docstring)rrrrr)__doc__rKr!r3r) rrrrrrQ func_namer[docs ````` r)boolean_dispatchr Ws - - - - - - - - -8#3#?   !go&Ao   !go&=CDDDBJ#   r Ir+c*eZdZdZdZdZdZdZdZdZ dS) FunctionModifierszn Used to denote the behavior of a function in TorchScript. See export() and ignore() for details. z:unused (ignored and replaced with raising of an exception)z>ignore (leave as a call to Python, cannot be torch.jit.save'd)z7export (compile this function even if nothing calls it)z>default (compile if called from a exported function / forward)zNif this method is not scripted, copy the python method onto the scripted modelzB_drop (function is fully ignored, declaration can be unscriptable)N) r3r!r4rUNUSEDIGNOREEXPORTDEFAULTCOPY_TO_SCRIPT_WRAPPER_DROPrr+r)r r s? JF MF FFNGX QEEEr+r c(tj|_|S)a This decorator indicates that a method on an ``nn.Module`` is used as an entry point into a :class:`ScriptModule` and should be compiled. ``forward`` implicitly is assumed to be an entry point, so it does not need this decorator. Functions and methods called from ``forward`` are compiled as they are seen by the compiler, so they do not need this decorator either. Example (using ``@torch.jit.export`` on a method): .. testcode:: import torch import torch.nn as nn class MyModule(nn.Module): def implicitly_compiled_method(self, x): return x + 99 # `forward` is implicitly decorated with `@torch.jit.export`, # so adding it here would have no effect def forward(self, x): return x + 10 @torch.jit.export def another_forward(self, x): # When the compiler sees this call, it will compile # `implicitly_compiled_method` return self.implicitly_compiled_method(x) def unused_method(self, x): return x - 20 # `m` will contain compiled methods: # `forward` # `another_forward` # `implicitly_compiled_method` # `unused_method` will not be compiled since it was not called from # any compiled methods and wasn't decorated with `@torch.jit.export` m = torch.jit.script(MyModule()) )r r_torchscript_modifierr[s r)exportrsT 17B Ir+ct|trK|}t|jdtj|jr t|jdtj|Stj|_|S)a This decorator indicates to the compiler that a function or method should be ignored and replaced with the raising of an exception. This allows you to leave code in your model that is not yet TorchScript compatible and still export your model. Example (using ``@torch.jit.unused`` on a method):: import torch import torch.nn as nn class MyModule(nn.Module): def __init__(self, use_memory_efficient): super().__init__() self.use_memory_efficient = use_memory_efficient @torch.jit.unused def memory_efficient(self, x): import pdb pdb.set_trace() return x + 10 def forward(self, x): # Use not-yet-scriptable memory efficient mode if self.use_memory_efficient: return self.memory_efficient(x) else: return x + 10 m = torch.jit.script(MyModule(use_memory_efficient=False)) m.save("m.pt") m = torch.jit.script(MyModule(use_memory_efficient=True)) # exception raised m(torch.rand(100)) r)r%propertysetattrfgetr r fsetr)r[props r)unusedrsP"h  I.0A0H    9   24E4L    07B Ir+c,eZdZdZdedededdfdZdS)_IgnoreContextManagerc dSr/r)r0rs r)rYz_IgnoreContextManager.__init__ r+exc_type exc_value tracebackrNcdSr/r)r0r!r"r#s r)__exit__z_IgnoreContextManager.__exit__ r r+)r3r!r4rYrr%rr+r)rrsS             r+rFc Ntr}tj|_|St t st d|dd}|rtj dt|nrtj dtfd}|S)a& This decorator indicates to the compiler that a function or method should be ignored and left as a Python function. This allows you to leave code in your model that is not yet TorchScript compatible. If called from TorchScript, ignored functions will dispatch the call to the Python interpreter. Models with ignored functions cannot be exported; use :func:`@torch.jit.unused ` instead. Example (using ``@torch.jit.ignore`` on a method):: import torch import torch.nn as nn class MyModule(nn.Module): @torch.jit.ignore def debugger(self, x): import pdb pdb.set_trace() def forward(self, x): x += 10 # The compiler would normally try to compile `debugger`, # but since it is `@ignore`d, it will be left as a call # to Python self.debugger(x) return x m = torch.jit.script(MyModule()) # Error! The call `debugger` cannot be saved since it calls into Python m.save("m.pt") Example (using ``@torch.jit.ignore(drop=True)`` on a method): .. testcode:: import torch import torch.nn as nn class MyModule(nn.Module): @torch.jit.ignore(drop=True) def training_method(self, x): import pdb pdb.set_trace() def forward(self, x): if self.training: self.training_method(x) return x m = torch.jit.script(MyModule()) # This is OK since `training_method` is not saved, the call is replaced # with a `raise`. m.save("m.pt") .. testcleanup:: import os os.remove('m.pt') zCArgument to @torch.jit.ignore must be a bool or a function but got drop_on_exportNzignore(drop_on_export=True) has been deprecated. TorchScript will now drop the function call on compilation. Use torch.jit.unused now. {})categoryzzignore(True) has been deprecated. TorchScript will now drop the function call on compilation. Use torch.jit.unused now. {}cRrtj|_ntj|_|Sr/)r r rr )r[drops r) decoratorzignore..decoratorns*  @'8'?B $ $'8'?B $ r+) callabler r rr%boolrKpopwarningswarn FutureWarning)r*rr[r'r+s` r)ignorer2sB~~#4#;  dD ! !  )"& ) )   ZZ 0$77N    @"        @"     r+c(tj|_|Sr/)r rrrs r)_dropr4xs06B Ir+c(tj|_|Sr/)r rrrs r)_copy_to_script_wrapperr6}s0GB Ir+ct|D]O}t||r=t||}t|rt |t jurdSPdS)NTF)rr$rGr,get_torchscript_modifierr r)modrJitems r)module_has_exportsr;sjC   3   3%%D~~ +D115F5MMM44 5r+c`t|}|dS|tjup |tjuSNF)r8r r r)r[rs r) should_dropr>s6 #B ' 'D |u $+ + Nt7H7N/NNr+ctt|}|tjup|tjup |tjuSr/)r8r r r rr[r9s r)rrsB "2 & &C  '' * #* * * #) )r+c<t|}|tjuSr/)r8r rr@s r) _is_drop_fnrBs "2 & &C #) ))r+cVttj||dtS)N)r)r%rgetattr_static staticmethodrr[s r) is_static_fnrGs$ g,S"dCCC\ R RRr+c6tj||jSr/)rrD__func__rFs r) get_static_fnrJs  !#r * * 33r+ct|sdSt|dr|j}t|dtjS)NrIr)r,r$rIrGr rrs r)r8r8sE B<<tr: [ 2.0A0I J JJr+c:t|}|dS||_dSr/)r8r)orignewrs r)copy_torchscript_modifierrOs' #D ) )D | $Cr+_overloaded_fnsaP Example usage of overload function: @torch.jit._overload def my_function(x: type0) -> type0: # decl 1 pass @torch.jit._overload def my_function(x: type1) -> type1: # decl 2 pass def my_function(x): # implementation if isinstance(x, type0): return x elif isinstance(x, type1): return x c t|\}}}d|dt|d|d|d d|zdztzS)NzImplementation for the z "zk" is missing. 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