Αi\%SSKJr SSKrSSKrSSKrSSKrSSKrSSKrSSKrSSK r SSK J r SSK J r SSKJrJrJr \(aSSKJrJr SSKJr \\\-S-rS\S 'SSjr&\ S 5r'S?S!jr(S@S"jr)SAS#jr*S@S$jr+SBS%jr,S&r-S'r."S(S)5r/\/"5r00r1S*\S+'S,r2S-r3S.r4S/S0.SCS1jjr5SDS2jr6SSS3S/S4.SES5jjr7SFS6jr8\ S7SS/S8.SGS9jj5r9SHS:jr:S;r;g)I) annotationsN)contextmanager)cache) TYPE_CHECKINGAnyLiteral) GeneratorIterable) TypeAliasr _ScopeTypestrc@[R"SUS3[SS9 g)NzThe interface 'z' is a fake implementation for torch compatibility. It does not have the actual functionality of PyTorch. 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(T  .9 rrzdict[str, types.ModuleType]rc[[RR55H?up[ U5(dM[ U[ 5(dM.[RU MA gr)rsysmodulesrrr r\rs r_clear_torch_proxy_modulesrsCS[[..01  D ! !j&E&E D!2rc[[RR55HWup[ U5(dM[ U[ 5(d[RU[U'[RU MY gr)rrrrrr r\rrs r_swap_torch_modules_to_cachersXS[[..01  D ! !fk22,/KK,=#D) D! 2rc[[5H8n[U5(d SUS35e[U[RU'M: g)N`z` is not a PyTorch module)rrrrrrs r_copy_torch_modules_from_cachersE()%%J4&0I'JJ%/5 D*rFrc^SU4Sjjn[[R;a[RU5 g[R(a!UbU"S5 [RU5 gUcU"S5 S[lgU[R :waU"S[R SUS35 [=R U-slg) NcB>T(ag[R"U5 gr)rr)msgrs r _warn_or_not2_modify_scope_of_torch_proxy.._warn_or_nots   crz=PyTorch already enabled globally, scope modification ignored.zAEnabling PyTorch compat globally, previous scope will be ignored.Tz0Extending PyTorch compat scope, previous scope: z , new scope: rE)r#r )TORCH_PROXY_FINDERr meta_pathrrr)rrr$s ` r_modify_scope_of_torch_proxyr(s  .%%e,++   O  %%e, } O 04, "777>?Q?f?f>ggtuzt{{| } ++u4+rcPUcg[U[5(aU1$[U5$r)r r rrs r _parse_scoper+s( }%w u:rrxrblocked_modulesbackendrcUS:Xd SU35e[U5nUb [U5 [U5n[5 [5 [ XS9 [ R RS[5 g)a Enable the PyTorch compat by adding the TorchProxyMetaFinder to sys.meta_path. This allows importing 'torch' modules that are actually proxies to PaddlePaddle. Args: scope (str or Iterable[str], optional): Specific module or modules to enable PyTorch compat for. If None, enables PyTorch compat globally. Defaults to None. blocked_modules (str or Iterable[str], optional): Specific module or modules to exclude from PyTorch compat. Defaults to None. backend (str, optional): The backend to enable compat for. Currently only "torch" is supported. Defaults to "torch". silent (bool, optional): If True, suppresses warnings about scope changes. Defaults to False. Example: .. code-block:: pycon :name: enable-compat-in-global-scope >>> import paddle >>> paddle.enable_compat() # Enable torch compat globally >>> import torch # type: ignore[import-not-found] # This will import paddle as torch >>> assert torch.sin is paddle.sin >>> paddle.disable_compat() # Disable torch compat .. code-block:: pycon :name: enable-compat-in-specific-scope >>> import paddle >>> paddle.enable_compat(scope={"triton"}) # Enable torch compat for 'triton' module only >>> import triton # type: ignore[import-untyped] # All `import torch` inside `triton` will proxy to paddle >>> try: ... import torch # type: ignore[import-not-found] # This will raise ModuleNotFoundError ... except ModuleNotFoundError: ... print("PyTorch compat is not enabled globally.") >>> paddle.disable_compat() # Disable torch compat rxzUnsupported backend: Nr r) r+"extend_torch_proxy_blocked_modulesrrr(rr'insertr&r,s renable_torch_proxyr2skV g @!6wi@@ "?3O"*?;  E " 6MM./rc[[R;a8[RR[5 [ 5 [ 5 g[ R"S5 g)a Disable the PyTorch proxy by removing the TorchProxyMetaFinder from sys.meta_path. This prevents 'torch' imports from being proxied to PaddlePaddle. Example: .. code-block:: pycon >>> import paddle >>> paddle.enable_compat() # Enable torch compat globally >>> import torch # type: ignore[import-not-found] # This will import paddle as torch >>> assert torch.sin is paddle.sin >>> paddle.disable_compat() # Disable torch compat >>> try: ... import torch # This will raise ModuleNotFoundError ... except ModuleNotFoundError: ... print("PyTorch compat is disabled.") Nztorch compat is not installed.)r&rr'removerrrrr$rrdisable_torch_proxyr5s?$S]]* /0"$&( MM23rT)rrrc#T# [U5n[[R;n[ [R 5n[R nX:Xa%U(aUbXA=(d [ 5:XaSv gU(a/[XS9 Sv U[lU[l[5 g[5 Sv [SSS9 U[lU[lg!U[lU[l[5 f=f![SSS9 U[lU[lf=f7f)a Context manager to temporarily enable or disable the PyTorch compat. When `enable` is True (default), the PyTorch compat is enabled for the duration of the context and restored to its previous state afterwards. When `enable` is False, the PyTorch compat is disabled for the duration of the context and restored afterwards. Args: enable (bool, optional): Whether to enable or disable the PyTorch compat within the context. Defaults to True. scope (str or Iterable[str], optional): Specific module or modules to enable PyTorch compat for. If None, uses the global scope. Defaults to None. silent (bool, optional): If True, suppresses warnings about scope changes. Defaults to False. Example: .. code-block:: pycon >>> import paddle >>> with paddle.compat.use_torch_proxy_guard(): ... # code that requires the Torch compat to be enabled ... import torch # type: ignore[import-not-found] ... ... assert torch.sin is paddle.sin ... # Temporarily disable the Torch compat ... with paddle.compat.use_torch_proxy_guard(enable=False): ... try: ... import torch ... except ModuleNotFoundError: ... print("Torch compat is disabled within this block.") ... # Torch compat is re-enabled here ... import torch ... ... assert torch.sin is paddle.sin N)rrT) r+r&rr'rrrr2r5)rrralready_has_torch_proxyoriginal_local_enabled_scopeoriginal_globally_enableds rrrsX  E0CMMA#&'9'N'N#O 2 D D ( "u} (^ce <  6 " -  34M  0  ! M  T$ 7,  34M  0-  34M  0  ! T$ 7,  34M  0s6BD( C +D(9D=!D("DD("D%%D(c.[RU5 g)a!Add modules to the PyTorch proxy blocked list. Modules in the blocked list will not use PyTorch compat when imported, and their functions will not trigger PyTorch compat when called. By default, some modules are already in the blocked list, such as 'tvm_ffi'. Args: modules(Iterable[str]): An iterable of module names to block from PyTorch compat. Example: .. code-block:: pycon >>> import paddle >>> paddle.enable_compat() # Enable torch compat globally >>> # Add 'my_custom_module' to the blocked list >>> paddle.compat.extend_torch_proxy_blocked_modules(['my_custom_module']) >>> # doctest: +SKIP('my_custom_module is not available') >>> import my_custom_module # type: ignore[import-not-found] # This import will not use torch compat N)rru)rs rr0r0]s* &&w/rc"[S1S9 SSKnU$)a Enable the triton support and return triton module. Args: None. Returns: triton module Example: .. code-block:: pycon >>> # doctest: +REQUIRES(env:GPU) >>> from paddle.compat import paddle_triton_fun >>> triton = paddle_triton_fun() >>> import triton.language as tl >>> @triton.jit >>> def add_kernel(X, Y, Z, N, BLOCK: tl.constexpr): ... pid = tl.program_id(0) ... offs = pid * BLOCK + tl.arange(0, BLOCK) ... mask = offs < N ... x = tl.load(X + offs, mask=mask) ... y = tl.load(Y + offs, mask=mask) ... tl.store(Z + offs, x + y, mask=mask) tritonr*rN)r2r<)r<s rpaddle_triton_funr=us.hZ( Mr)rr )r&zdict[str, Any])rerkrlNone)rr rr rlr)rr rlr)rr rrrlr)rr rlr)rrrrrlr>)rzstr | Iterable[str] | Nonerlr) rr r-r r.zLiteral['torch']rrrlr>)rlr>)rrrr rrrlzGenerator[None, None, None])rz Iterable[str]rlr>)< __future__rrH importlib.abcimportlib.utilrr|rrr contextlibr functoolsrtypingrrrcollections.abcr r typing_extensionsr r r rrr(r.r0r=rRrr\rnrrqrsrvrrrrrrrrrr&rrrrr(r+r2r5rr0r=r$rrrGs'# %..3+(3-/$6J 6!"" $7 04%""4&/0KL40 #<C;!939'-' ' 44:;?  x x v*+3505" "65 5 5 5D"& ' 30 30 30 30  30  30l44 HM HM HM  HM ! 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