PhddlZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl m Z m Z m Z mZmZmZmZddlZddlZddlmcmZddlmZddlmZddlmZddlmZddl m!Z!m"Z"m#Z#de$fd Z%d ejLd e'fd Z(d ddejRjTdee dfde e$e fde'd e f dZ+d ddejRjTdee dfde e$e fde'd df dZ,d ddejRjTdee dfde e$e fde'd df dZ-d ddejRjTdee dfde e$e fde'de'd e f dZ.de d e fdZ/e+e,e-ej`e.dej`e.d dZ1dZ2gdZ3dde3fde d ee$d!ee$d"e e$e fd#ee$d df d$Z4d%Z5d&Z6d!e$d dfd'Z7d(d)d#ee$de d dfd*Z8d e'fd+Z9ejtZ;de;_<d,Z=Gd-d.eZ>dAd/Z? dBd0d d1dejRjdee dfdee e$e fd#ee$ee$fd2e'd e e$e$ff d3ZAGd4d5eBZCdd6d7e$dejRjTdee dfde e$e fd8e'd9e'd e$fd:ZDdejRjd ejRjTfd;ZFdZId?e2ZJGd@d)ZKy)CN)AnyCallableDictListOptionalTupleUnion) clone_input)SchemaCheckMode)get_file_path_2)TorchFunctionMode)aot_autograd_checkautograd_registration_check fake_checkreasonc d}|S)Ncd|_|S)NT)"_torch_dont_generate_opcheck_tests)funs yC:\Users\daisl\Desktop\realtime-object-detection\venv\Lib\site-packages\torch/testing/_internal/optests/generate_tests.pyinnerz'dontGenerateOpCheckTests..inners15. )rrs rdontGenerateOpCheckTestsrs Lrtensorreturncr|jrytjjj |ryy)NTF)is_metatorch _subclasses fake_tensoris_fake)rs r is_abstractr#%s, ~~ $$,,V4 rT copy_inputsopargs.kwargsr%c|rt||f\}}tjtjt ||fryt 5||i|}|cdddS#1swYyxYwN)deepcopy_tensorspytree tree_any_onlyrTensorr#r )r&r'r(r%results rsafe_schema_checkr0-sZ'v7 f ELL+f~F  T$V$   s AA&ctjtjt||fry|rt ||f\}}tjtjd||fsyt |||S)Nc|jSr*) requires_grad)xs rz2safe_autograd_registration_check..Jsr)r,r-rr.r#r+rr&r'r(r%s r safe_autograd_registration_checkr7=shELL+f~F'v7 f    /$   &r4 88rctjtjt||fry|rt ||f\}}t |||Sr*)r,r-rr.r#r+rr6s rsafe_fake_checkr9PsEELL+f~F'v7 f b$ ''rdynamicctjtjt||fryfd}t ||||dS)Nctjtjtj||f\}}|i|Sr*)r, tree_map_onlyrr.clone)r'r(r&s rfuncz%safe_aot_autograd_check..funcks7++ELL%++f~V f4"6""rauto)check_gradients)r,r-rr.r#r)r&r'r(r:r%r?s` rsafe_aot_autograd_checkrB^s<ELL+f~F# dD&'6 RRrinputscTtjtjt|Sr*)r,r=rr.r )rCs rr+r+ts    k6 BBrF)r:) test_schematest_autograd_registrationtest_faketensortest_aot_dispatch_statictest_aot_dispatch_dynamiczThttps://docs.google.com/document/d/1Pj5HRZvdOq3xpFpbEjUZp2hBovhy7Wnxw14m6lF2154/edittestcase namespacesfailures_dict_pathadditional_decorators test_utilsc itDcgc]*}|jdrtt|r|,}}_t j j }t j|d}ttjj|dtjtt|t!fd} |D cic] } | t"| }} |D]$} |j%D]\} } | | | | &t'ycc}wcc} w)aGiven an existing TestCase, use the existing tests to generate additional validation tests for custom operators. For {all existing tests in the TestCase} x {all test utils}, we will generate one new test. The new test runs a TorchFunctionMode that intercepts ``op(*args, **kwargs)`` calls and invokes ``test_util(op, *args, **kwargs)``, where ``op`` is an operator. The test_util that we support are in ALL_TEST_UTILS. They are: - test_schema: This runs SchemaCheckMode. - test_autograd_registration: This runs autograd_registration_check. - test_faketensor: This runs CrossRefFakeMode. - test_aot_dispatch_static: This runs aot_autograd_check, which: checks that the outputs (and gradients, if they are computable) are the same under eager-mode PyTorch and using AOTAutograd. - test_aot_dispatch_dynamic: Same as aot_dispatch_static, but runs AOTAutograd using dynamic shapes instead of static shapes. The generated test will have name ``{test_util}__{original_name}``. For example, if there is a method named ``test_cumsum``, then we will generate a ``test_schema__test_cumsum``, ``test_faketensor__test_cumsum``, etc. For more details, see https://docs.google.com/document/d/1Pj5HRZvdOq3xpFpbEjUZp2hBovhy7Wnxw14m6lF2154/edit Args: testcase: The testcase we will modify and generate additional tests for. namespaces: We will only intercept calls to custom operators with these namespaces. failures_dict_path: See ``validate_failures_dict_structure`` for more details test_utils: a list of test_utils to generate. Example: ["test_schema", "test_faketensor"] Ntest_rzfailures_dict.json create_filec 4 t| t ddrydz|z tj   fd}|jj dx}rddl}d}|D]+}t ||js|jdk(s*d}-|rg}|D]}t ||jru|jd k(rf|j\} } |jrJd | d k7r?|j|jj| tt| f|j|||jd< vr D] } | |} t! rt#d d d dt% |y)NrF__c t  jd5|i|}ddd|S#1swYSxYw)N.) OpCheckMode__name__) r'r(r/ failures_dictrLmethodrKnew_method_nameprefixrJtesters r new_methodzDgenerate_opcheck_tests..construct_method..new_methodsZ$$%Q&78"  00MMs 4> pytestmarkropcheck_only_oneT parametrizeNYIdevicezTried to autogenerate z but z already has method named z4. Please rename the original method on the TestCase.)getattr functoolswraps__dict__getpytest isinstanceMarknamer'r(appendmarkranextiterhasattr RuntimeErrorsetattr)attrr\r]r^r_rir`rnnew_pytestmarkargnames argvaluesdecrZr[rMrYrLrKrJs `` @@rconstruct_methodz0generate_opcheck_tests..construct_methods4( 6? G  4-$.     ! $,,00> >: >  % "dFKK0TYYBT5T'+$# !#&D!$ 4m9S.2ii+)#';;55$x/*11 & 7 7$,tDO/D.F!" %"))$/'5C ##L1 3 3,_= _ > 8_ -((9xjI$$3#45*+  /:6r)dir startswithcallablerdinspect currentframef_back getframeinfor ospathdirname FailuresDictloadshould_update_failures_dict validate_failures_dict_structure!validate_failures_dict_formattingALL_TEST_UTILSitemsgenerate_tag_tests)rJrKrLrMrNm test_methods prev_framefilenameryrlrtr\r]rYs```` @rgenerate_opcheck_testsrsON$ "XA << Xgh.B%C  !))+22 '' 3A6, GGOOH %'; !%%(C(E&M%]JI%&899797v:DD$t,,JD(..0NFF T66 21x0EFg\Es /D7-D<cd}|jjD]\}}|jDcgc]\}}d|vr |ddk(r|}}}t|dkD} ||| |} |jddjdd} d | z} | |vr|| D] } | | } t || rt d | d t || | ycc}}w) Ncfd}|S)Nc( tjjj}tjj|jv}|sysytddd#t$r}t j d|d}~wwxYw)NzCan't import operator zop 'za' was tagged with torch.Tag.pt2_compliant_tag but it failed some of the generated opcheck tests (z?). This may lead to silent correctness issues, please fix this.) r_libraryutils lookup_opAttributeErrorunittestSkipTestTagpt2_compliant_tagtagsAssertionError)selfr&eop_marked_as_compliantdefinitely_not_pt2_compliantqualname xfailed_testss rrz8generate_tag_tests..generate_test..inners T^^))33H=&+YY%@%@BGG%K ")/ xj!!?##$ " T''*@ (KLRSS Ts)A** B3B  Br)rrrrs``` r generate_testz)generate_tag_tests..generate_tests $ rrHstatusxfailr::_rVtest_pt2_compliant_tag_zTried to generate a test named z, but it exists already. This could be because of a name collision (where we generated two tests with the same name), or where we generated a test with the same name as an existing test.)datarlenreplacerqrrrs)rJrYrMrr test_dicttest status_dictrr generatedmangled_qualname test_name decorators rrrs* -11779)&/__%6 %6!k*5H%0 %6  (+='9A'=$!(,H-X $++D#6>>sCH-0@@  - -29= %i0 > 8Y '1)=KL  )Y/; : sC)rskipxsuccessct|5}|j}dddtj|}|j d}|k(ryt r&tj|}|j y|jd}|jd}tj||}dj|}td|d#1swYxYw)NT)to_str z Expected the failures dict to be formatted a certain way. Please see the above diff; you can correct this either manually or by re-running the test with PYTORCH_OPCHECK_ACCEPT=1) openreadrr_saversave splitlinesdifflib unified_diffjoinrr)rLfpactualrYexpecteddiffs rrrPs  !R " %%&89M""$"/H "$$))*<= ""1%H   q !F    1D 774=D  TF# $  " !s CC# failure_dictrc |j}t|j}|jD]E}t|j}|j D]\}}t |jt ddhk7r t d|d}|tvrt d|dt|jd\} t fd|Dst d|d ||D]}} j| s t| d zd } tjd d | } |j| k7rMt|| rZt d|d| d| d| d|jd Hy )aValidates the failures dict. The failure dict looks something like the following. It maps operator name (qualname) to a list of autogenerated tests. Each autogenerated test may have a check for the operator (if the operator is called by the test); the dictionary specifies if we should skip the check, or if we expect some check to fail. { "fbgemm::split_lengths": { "test_schema__test_split_lengths": { "comment": "you can put whatever you want into the comment section", "status": "xfail", } "test_schema__test_split_lengths_empty": { "comment": "", "status": "skip", }, }, "fbgemm::gather_lengths": { "test_schema__test_gather_lengths": { "comment": "", "status": "skip", }, }, } commentrzGin failures_dict, expected sub-dict to have keys 'comment' and 'status'zIn failures_dict, got status=z but it needs to be in rVc3@K|]}j|ywr*)r{).0ractual_test_names r z3validate_failures_dict_structure..sPZT'2248ZszIn failures_dict, test name 'z' should begin with one of Nz\[.*\]rz!In failures dict, got test name 'z#'. We parsed this as running test 'z' on 'z', but z! does not exist on the TestCase 'z*]. Maybe you need to change the test name?)rlistkeysvaluesrsetrr TEST_OPTIONSsplitanyr{rresubrXrq) rrNrJ qualnamestest_to_option test_namesrr test_option test_classrbase_test_namers @rrrgs> $$L\&&()I&--/.--/0 $2$8$8$: Iy9>>#$Y,A(BB"]$H-K,."3K=@WXdWef,5??3+? (J(PZPP"3I;>YZdYef#'2248!1#d)a-/!B!# 2~!F$$ 28^4"7 {C%%)F&0@%&&GHYHYGZ[>?#%;0rcZd}|tjvxrtj|dk(S)NPYTORCH_OPCHECK_ACCEPT1renviron)keys rrrs( "C "**  7CC!77rc"tjSr*)_is_inside_opcheck_modevaluerrris_inside_opcheck_moders " ( ((rc heZdZdZdeedededddedef d Zdd Zfd Z fd Z d Z ddZ xZ S)rWz For a given test, OpCheckMode intercepts calls to operators and runs test_util(op, args, kwargs) for each intercepted (op, args, kwargs). rKtest_util_name test_utilrYrrrLcf||_||_||_||_||_||_i|_yr*)rKrrrrYrLseen_ops_to_errors)rrKrrrYrrLs r__init__zOpCheckMode.__init__s?%#,"+"4#%rc |jjD]}|jj||j}t |j|dk(sEt r*|jj||jddn4|dk(r/td|d|jd|jd tg}|jjD][}|jj||j}|dk7r/t |j|dk(rK|j|]|syt r/|D])}|jj||jd+y|j|dd\}}}}t|j|||t }td |jd |d td||)Nrrrrrz8generate_opcheck_tests: Unexpected success for operator z on test z. This may mean that you have fixed this test failure. Please rerun the test with PYTORCH_OPCHECK_ACCEPT=1 to automatically update the test runner or manually remove the expected failure in the failure dict at zFor more details, see ) save_dataz,Test generated by `generate_opcheck_tests`, z, failed on operators z. This usually means that the operators are not implemented correctly and may lead to silently incorrect behavior. Set PYTORCH_OPCHECK_PRINT_BETTER_REPRO=1 for a standalone repro, or please see zX for more recommendations. To reproduce this problem locally, try to run the following: )rrrY get_statusrrr set_status OpCheckErrorrLGDOCrmgenerate_reprorshould_print_better_repro) rroption failed_opsr&exr'r( repro_commands rmaybe_raise_errors_on_exitz&OpCheckMode.maybe_raise_errors_on_exits//446H''228T^^LF4**845:.0&&11 $..*b2(*V'j $..1ABG $6674#f&  )7* //446H''228T^^LF#4**845:   h ' 7  & ( ""--b$..'J!  $66z!}EaHBf&   T6=V=X :4>>:JK##-,/fMMZO ]   rctj|_tjj dd|_dt_dtjd<t| |i|S)NTORCHDYNAMO_DISABLErTr) rrprev_is_opcheck_moderrrhprev_dynamo_disablesuper __enter__)rr'r( __class__s rrzOpCheckMode.__enter__sV$;$A$A!#%::>>2G#L (,%,/ ()w $1&11rc|jt_|jtj d< |j tr|jjt|,|i|}|S#t|,|i|}wxYw)Nr) rrrrrrrrrYrr__exit__)rr'r(r/rs rrzOpCheckMode.__exit__s(,(A(A%,0,D,D () 7  + + -*,""'')W%t6v6F W%t6v6Fs 4A::B c |j|||dy#tjjj$rYywxYw)NFr$)rrr r!UnsupportedFakeTensorException)rr&r'r(s r run_test_utilzOpCheckMode.run_test_util#sA  NN2tVN ?  ,,KK    s'AAc|r|ni}t|tjjtjjfs||i|Stj j sS>S TU(( ( II "yy%%'}}))+(( ( dEJJ77 83D9D99; ^^D !! $ T__ $(( (+T6N;t&v&##..xH Z 6W#4 U4#:#::8:D++H5""4: v    U,.++H5<$AG99G>rN)rN)rX __module__ __qualname____doc__rstrrrrrrrr __classcell__)rs@rrWrWse %I%% % & %  % %66p2 'rrWcjd}|tjvrytj|}|dk(xs|dk(S)aIf set, the tests generated by `generate_opcheck_tests` will print a repro command on failure. In order to print the repro command, we need to save some tensors to disk. These will be saved under the following directory: {tempfile.gettempdir()}/pytorch_opcheck_safe_to_delete/. Although this is a temp folder, it will usually not automatically get cleaned up, so you'll need to manually delete it. "PYTORCH_OPCHECK_PRINT_BETTER_REPROFrrr)rrs rrrWs8 /C "** JJsOE C< %5A:%rALL)rNraise_exceptionr!c |i}t|tjjr t |}t|tjj st dt||dk(rttj}t|tr|f}t|ttfr,t|jtjs-t d|dttjdi}|D]}t|} ||||d||<|S#t$r$}|rt!d|d |d ||||<Yd}~Hd}~wwxYw) a Given an operator and some sample arguments, tests if the operator is registered correctly. We test the following (which are important for correctness in eager-mode PyTorch and with torch.compile): - test_schema: if the operator's schema is correct. - test_autograd_registration: if autograd was registered correctly, i.e. to the correct DispatchKey. - test_faketensor: If the operator has a FakeTensor implementation (and if it is correct). - test_aot_dispatch_static: If the operator works with AOTAutograd/AOTDispatch, which is one of the parts in the PT2 stack. Checks that the outputs (and gradients, if they are computable) of the operator are the same under eager-mode PyTorch and torch.compile. - test_aot_dispatch_dynamic: Same as aot_dispatch_static, but tests dynamic shapes instead of static shapes. For best results, please call ``opcheck`` multiple times with a representative set of inputs. For example, if your operator supports autograd, please use ``opcheck`` with inputs that require_grad. Args: op: The operator. Should look like torch.ops.aten.foo args: The args to the operator kwargs: The kwargs to the operator test_utils: Tests that we should run. Default: all of them. Example: ["test_schema", "test_faketensor"] raise_exception: If we should raise an exception on the first error. If False, we will return a dict with information on if each test passed or not. Nzeopcheck(op, ...): op must be instance of torch._ops.OpOverload, e.g. torch.ops.aten.sin.default, got r zopcheck(op, ..., test_utils=z'), expected test_utils to be subset of z but it was notSUCCESSzopcheck(op, ...): z failed with z (scroll up for stack trace))rjrr r rr  ValueErrortypetuplerrrrrissubsetrr) r&r'r(rNr! results_dictrr]rs ropcheckr)iszR~"ejj112 -b 1 b%**// 0448H: ?  U>..01 *c" ] j5$- 0J8P8P9*:,7$^%8%8%:;c&BC77>>$' D! JJf~x 03H:R@  4 zz$$T*HBH QtfAhZ0 -1157H I" rc 8tjj|j}t |dk7r3t d|jd|Dcgc]}|j c}|dj }|dk(r |jSt||Scc}w)NrzSopcheck can only test operators without overloads. Got the following overloads for z: rr) r_C_jit_get_schemas_for_operator_qualified_op_namerrr overload_namedefaultrd)r& all_schemasschemar@s rrrs((889N9NOK ;1//1/D/D.ER3>?;$$;?@ B   N00Mzz 2} %% @sBr)indent sort_keysrzsThis is a dict containing failures for tests autogenerated by generate_opcheck_tests. For more details, please see c eZdZdedefdZeddddZddeefdZ dd Z d ed edefd Z d dd ed ededeefdZ y )rrrc ||_||_yr*)rr)rrrs rrzFailuresDict.__init__ s  rFrQrc|rAtjj|s"t|i}tj |St |5}|j }|jdk(rtitd}n-tj|}d|vsJd|vr |dtk(sJdddt|dS#1swYxYw)Nr _descriptionr_versionrrK) rrr4rrrrstrip DESCRIPTIONVERSIONjsonloads)rrRr/rcontentsdcts rrzFailuresDict.loads rww~~d3!$+F    M $Z2wwyH~~2%$/ ' jj*}$}!S(S_-GGGD#f+..Zs A CCct|jtd}tj|fit dz}|r|St |jd5}|j|dddy#1swYyxYw)NrIrw) rMrrNrOdumps DUMP_OPTIONSrrwrite)rrto_dump serializedrs rrzFailuresDict._save%sf'II ZZ8<84?   $))S !R HHZ ""s A++A4Nc"|jSr*)r)rs rrzFailuresDict.save4szz|rrrcX||jvry|j|}||vry||dS)Nrrr)rrrrRs rrzFailuresDict.get_status7s9 499 $ii! C 9~h''rrrrc||jvri|j|<|j|}||vrddd||<|dk(r||=y|||d<| |||d<yy)Nr)rrrrrr\)rrrrrrRs rrzFailuresDict.set_status?sx 499 $"$DIIh ii! C (,ros DDD $$+?1-S     S/  cN     * 9 9 S/9 cN9  9  90 (  ( S/ ( cN (  (  (( S S S/S cNS S  S S,CSCSC%"B& 1 1 1!"3!2!2" ^)-15. |G|GS |G! |G X . |G S |G  |G~30l- #$.A A.23iACFA AH8T8 *)//+ %)\#\~&*(,K ). K K S/K T#s(^ $K c49n% K  K #s(^K\ 9 / / / S// cN /  // /d& ##& ZZ&"$/ T#tCH~"5667 $$(6+ G4G4r