%`iddlmZddlmZmZmZmZddlZddlmZddl m Z ddl m Z Gdde ZGd d e ZGd d e ZGd de ZdS))Sequence)AnyCallableOptionalUnionN)nn) transforms) TransformcTeZdZdZdeeddffd ZdedefdZde fdZ xZ S) ComposeaComposes 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 returnNctt|tst d|st d||_dSN5Argument transforms should be a sequence of callablesPass at least one transform)super__init__ isinstancer TypeError ValueErrorr selfr __class__s x/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torchvision/transforms/v2/_container.pyrzCompose.__init__)s\ *h// <STT T <:;; ;$inputscXt|dk}|jD]}||}|r|n|f}|SN)lenr rrneeds_unpacking transformoutputss rforwardzCompose.forward1sGf++/ @ @Ii(G /?WWgZFFrctg}|jD]}|d|d|SNz  r appendjoinr format_stringts r extra_reprzCompose.extra_repr8G  - -A   , , , ,yy'''r) __name__ __module__ __qualname____doc__rrrrr%strr/ __classcell__rs@rr r s:%8H#5%$%%%%%%ss(C((((((((rr ceZdZdZejZd deee e j fde ddffd Z deeeffdZd edefd Zdefd ZxZS) RandomApplyaApply 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 pr Nc"tt|ttjfst d|std||_d|cxkrdksntd||_ dS)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 r;)rr r;rs rrzRandomApply.__init__Us *x&?@@ <hii i <:;; ;$qC_`` `rc |j|jdS)Nr r;r?)rs r _extract_params_for_v1_transformz,RandomApply._extract_params_for_v1_transformbs"oDF;;;rrct|dk}tjd|jkr |r|n|dS|jD]}||}|r|n|f}|S)Nrr)r torchrandr;r r!s rr%zRandomApply.forwardesof++/ :a==DF " ",;66&) ; @ @Ii(G /?WWgZFFrctg}|jD]}|d|d|Sr'r)r,s rr/zRandomApply.extra_reprpr0r)r:)r1r2r3r4 _transformsr9_v1_transform_clsrrrrr=floatrdictr5rr@r%r/r6r7s@rr9r9?s&$/  5();R])J#K PU `d      <$sCx.<<<< s s    (C((((((((rr9cheZdZdZ d deedeeeddffd Z de de fdZ xZ S) RandomChoiceaApply single transformation randomly picked from a list. This transform does not support torchscript. Args: transforms (sequence or torch.nn.Module): list of transformations p (list of floats or None, optional): probability of each transform being picked. If ``p`` doesn't sum to 1, it is automatically normalized. If ``None`` (default), all transforms have the same probability. Nr r;r ct|tstd|std|dgt |z}nOt |t |kr/tdt |dt |t ||_t|fd|D|_ dS)Nrrrz4Length of p doesn't match the number of transforms: z != cg|]}|z SrM).0probtotals r z)RandomChoice.__init__..s---4$,---r) rrrrr rrr sumr;)rr r;rPrs @rrzRandomChoice.__init__s *h// <STT T <:;; ; 9c*oo%AA VVs: & &qTWXYTZTZqq`cdn`o`oqqrr r $A----1---rrcttjtj|jd}|j|}||Sr)intrB multinomialtensorr;r )rridxr#s rr%zRandomChoice.forwardsA%#EL$8$8!<<==OC( y&!!r)N) r1r2r3r4rrrlistrGrrr%r6r7s@rrJrJws  $(..X&. DK .  ......("s"s""""""""rrJcHeZdZdZdeeddffd ZdedefdZxZ S) 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 r Nct|tstd|stdt ||_dSr)rrrrrrr rs rrzRandomOrder.__init__s\*h// <STT T <:;; ; $rrct|dk}tjt|jD]}|j|}||}|r|n|f}|Sr)r rBrandpermr )rrr"rWr#r$s rr%zRandomOrder.forwardsef++/>#do"6"677 @ @C,Ii(G /?WWgZFFr) r1r2r3r4rrrrr%r6r7s@rrZrZs|%8H#5%$%%%%%%ssrrZ)collections.abcrtypingrrrrrBr torchvisionr rEtorchvision.transforms.v2r r r9rJrZrMrrrbs/$$$$$$111111111111 111111//////1(1(1(1(1(i1(1(1(h5(5(5(5(5()5(5(5(p#"#"#"#"#"9#"#"#"L)r