EiSSKJr SSKJrJrJrJr SSKrSSKJr SSK J r SSK J r "SS\ 5r"S S \ 5r"S S \ 5r"S S\ 5rg))Sequence)AnyCallableOptionalUnionN)nn transforms) Transformc^^\rSrSrSrS\\SS4U4SjjrS\S\4Sjr S\ 4S jr S r U=r $) Compose a_Composes several transforms together. This transform does not support torchscript. Please, see the note below. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example: >>> transforms.Compose([ >>> transforms.CenterCrop(10), >>> transforms.PILToTensor(), >>> transforms.ConvertImageDtype(torch.float), >>> ]) .. note:: In order to script the transformations, please use ``torch.nn.Sequential`` as below. >>> transforms = torch.nn.Sequential( >>> transforms.CenterCrop(10), >>> transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)), >>> ) >>> scripted_transforms = torch.jit.script(transforms) Make sure to use only scriptable transformations, i.e. that work with ``torch.Tensor``, does not require `lambda` functions or ``PIL.Image``. r returnNc>[TU]5 [U[5(d [ S5eU(d [ S5eXlgN5Argument transforms should be a sequence of callablesPass at least one transform)super__init__ isinstancer TypeError ValueErrorr selfr __class__s a/home/mande/repo/quber/.venv/lib/python3.13/site-packages/torchvision/transforms/v2/_container.pyrCompose.__init__)s; *h//ST T:; ;$inputscj[U5S:nURHnU"U6nU(aUOU4nM W$N)lenr rrneeds_unpacking transformoutputss rforwardCompose.forward1s9f+/I(G /WgZF)rcv/nURHnURSU35 M SRU5$Nz  r appendjoinr format_stringts r extra_reprCompose.extra_repr88 A  4s ,!yy''rr )__name__ __module__ __qualname____firstlineno____doc__rrrrr(strr3__static_attributes__ __classcell__rs@rr r sD:%8H#5%$%ss(C((rr c^\rSrSrSr\R rS S\\ \ \ R4S\ SS4U4SjjjrS\\\44SjrS \S\4S jrS\4S jrS rU=r$) RandomApply?aApply randomly a list of transformations with a given probability. .. note:: In order to script the transformation, please use ``torch.nn.ModuleList`` as input instead of list/tuple of transforms as shown below: >>> transforms = transforms.RandomApply(torch.nn.ModuleList([ >>> transforms.ColorJitter(), >>> ]), p=0.3) >>> scripted_transforms = torch.jit.script(transforms) Make sure to use only scriptable transformations, i.e. that work with ``torch.Tensor``, does not require `lambda` functions or ``PIL.Image``. Args: transforms (sequence or torch.nn.Module): list of transformations p (float): probability of applying the list of transforms r prNc>[TU]5 [U[[R 45(d [ S5eU(d [S5eXlSUs=::aS::d O [S5eX l g)NzJArgument transforms should be a sequence of callables or a `nn.ModuleList`rgg?z@`p` should be a floating point value in the interval [0.0, 1.0].) rrrrr ModuleListrrr rB)rr rBrs rrRandomApply.__init__Us` *x&?@@hi i:; ;$qC_` `rc4URURS.$)Nr rBrG)rs r _extract_params_for_v1_transform,RandomApply._extract_params_for_v1_transformbs"ooDFF;;rrc[U5S:n[R"S5UR:aU(aU$US$URHnU"U6nU(aUOU4nM W$)Nr"r)r#torchrandrBr r$s rr(RandomApply.forwardes^f+/ ::a=DFF ",6 ;&) ;I(G /WgZF)rcv/nURHnURSU35 M SRU5$r+r-r0s rr3RandomApply.extra_reprpr5rrBr )g?)r6r7r8r9r: _transformsr@_v1_transform_clsrrrrrDfloatrdictr;rrHr(r3r<r=r>s@rr@r@?s&$// 5();R]])J#K PU `d  <$sCx.< s s (C((rr@cf^\rSrSrSrS S\\S\\\ SS4U4Sjjjr S\ S\ 4S jr S r U=r$) RandomChoicewaApply single transformation randomly picked from a list. This transform does not support torchscript. Args: transforms (sequence or torch.nn.Module): list of transformations p (list of floats or None, optional): probability of each transform being picked. If ``p`` doesn't sum to 1, it is automatically normalized. If ``None`` (default), all transforms have the same probability. Nr rBrc>[U[5(d [S5eU(d [S5eUcS/[ U5-nO;[ U5[ U5:wa#[S[ U5S[ U535e[ TU]5 Xl[U5nUVs/sHoDU- PM snUl gs snf)Nrrr"z4Length of p doesn't match the number of transforms: z != ) rrrrr#rrr sumrB)rr rBtotalprobrs rrRandomChoice.__init__s *h//ST T:; ; 9c*o%A Vs: &STWXYTZS[[_`cdn`o_pqr r $A+,-14,1--s%B<rc[[R"[R"UR5S55nUR UnU"U6$r!)intrK multinomialtensorrBr )rridxr&s rr(RandomChoice.forwards?%##ELL$8!<=OOC( &!!rrP)N)r6r7r8r9r:rrrlistrSrrr(r<r=r>s@rrVrVwsY $(.X&. DK .  ..("s"s""rrVcP^\rSrSrSrS\\SS4U4SjjrS\S\4Sjr S r U=r $) RandomOrderzApply a list of transformations in a random order. This transform does not support torchscript. Args: transforms (sequence or torch.nn.Module): list of transformations r rNc>[U[5(d [S5eU(d [S5e[TU]5 Xlgr)rrrrrrr rs rrRandomOrder.__init__s;*h//ST T:; ; $rrc[U5S:n[R"[UR55H#nURUnU"U6nU(aUOU4nM% W$r!)r#rKrandpermr )rrr%rar&r's rr(RandomOrder.forwardsUf+/>>#doo"67C,I(G /WgZF8rr ) r6r7r8r9r:rrrrr(r<r=r>s@rreres8%8H#5%$%ssrre)collections.abcrtypingrrrrrKr torchvisionr rQtorchvision.transforms.v2r r r@rVrerrrqsM$11 1/1(i1(h5()5(p#"9#"L)r