\hSSKJr 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 $) Compose a_Composes several transforms together. This transform does not support torchscript. Please, see the note below. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example: >>> transforms.Compose([ >>> transforms.CenterCrop(10), >>> transforms.PILToTensor(), >>> transforms.ConvertImageDtype(torch.float), >>> ]) .. note:: In order to script the transformations, please use ``torch.nn.Sequential`` as below. >>> transforms = torch.nn.Sequential( >>> transforms.CenterCrop(10), >>> transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)), >>> ) >>> scripted_transforms = torch.jit.script(transforms) Make sure to use only scriptable transformations, i.e. that work with ``torch.Tensor``, does not require `lambda` functions or ``PIL.Image``. r returnNc>[TU]5 [U[5(d [ S5eU(d [ S5eXlg)N5Argument transforms should be a sequence of callableszPass at least one transform)super__init__ isinstancer TypeError ValueErrorr selfr __class__s ^/var/www/fran/franai/venv/lib/python3.13/site-packages/torchvision/transforms/v2/_container.pyrCompose.__init__)s; *h//ST T:; ;$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&strr1__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 [ S5eXlSUs=::aS::d O [S5eX l g)NzJArgument transforms should be a sequence of callables or a `nn.ModuleList`gg?z@`p` should be a floating point value in the interval [0.0, 1.0].) rrrrr ModuleListrr rr@)rr r@rs rrRandomApply.__init__UsQ *x&?@@hi i$qC_` `rc4URURS.$)Nr r@rE)rs r _extract_params_for_v1_transform,RandomApply._extract_params_for_v1_transform`s"ooDFF;;rrc[U5S:n[R"S5UR:aU(aU$US$URHnU"U6nU(aUOU4nM W$)Nr r)r!torchrandr@r r"s rr&RandomApply.forwardcs^f+/ ::a=DFF ",6 ;&) ;I(G /WgZF)rcv/nURHnURSU35 M SRU5$r)r+r.s rr1RandomApply.extra_reprnr3rr@r )g?)r4r5r6r7r8 _transformsr>_v1_transform_clsrrrrrBfloatrdictr9rrFr&r1r: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$) RandomChoiceuaApply 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 r@rc^>[U[5(d [S5eUcS/[U5-nO;[U5[U5:wa#[ S[U5S[U535e[ TU]5 Xl[U5nUVs/sHoDU- PM snUl gs snf)Nrr z4Length of p doesn't match the number of transforms: z != ) rrrr!rrrr sumr@)rr r@totalprobrs rrRandomChoice.__init__s *h//ST T 9c*o%A Vs: &STWXYTZS[[_`cdn`o_pqr r $A+,-14,1--sB*rc[[R"[R"UR5S55nUR UnU"U6$r)intrI multinomialtensorr@r )rridxr$s rr&RandomChoice.forwards?%##ELL$8!<=OOC( &!!rrN)N)r4r5r6r7r8rrrlistrQrrr&r:r;r<s@rrTrTusY $(.X&. DK .  ..&"s"s""rrTcP^\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 rNcn>[U[5(d [S5e[TU]5 Xlg)Nr)rrrrrr rs rrRandomOrder.__init__s,*h//ST T $rrc[U5S:n[R"[UR55H#nURUnU"U6nU(aUOU4nM% W$r)r!rIrandpermr )rrr#r_r$r%s rr&RandomOrder.forwardsUf+/>>#doo"67C,I(G /WgZF8rr ) r4r5r6r7r8rrrrr&r:r;r<s@rrcrcs8%8H#5%$% ssrrc)collections.abcrtypingrrrrrIr torchvisionr rOtorchvision.transforms.v2r r r>rTrcrrrosM$11 1/1(i1(h3()3(l""9""J)r