hSrSSKJr SSKrSSKJr SSKJr SSKrSSK J r "SS\ \ \S 4\R\5r g) zPImplementation of a space that represents the cartesian product of other spaces.) annotationsN)Iterable)Any)Spacec^\rSrSrSrSSU4Sjjjr\S5rSSU4SjjjrSSSjjr SSjr SSjr SS jr SS jr SS jrSS jrSS jrSrU=r$)TupleaA tuple (more precisely: the cartesian product) of :class:`Space` instances. Elements of this space are tuples of elements of the constituent spaces. Example: >>> from gymnasium.spaces import Tuple, Box, Discrete >>> observation_space = Tuple((Discrete(2), Box(-1, 1, shape=(2,))), seed=42) >>> observation_space.sample() (np.int64(0), array([-0.3991573 , 0.21649833], dtype=float32)) c>[U5UlURH-n[U[5(aMUS[ U535e [ TU]SSU5 g)apConstructor of :class:`Tuple` space. The generated instance will represent the cartesian product :math:`\text{spaces}[0] \times ... \times \text{spaces}[-1]`. Args: spaces (Iterable[Space]): The spaces that are involved in the cartesian product. seed: Optionally, you can use this argument to seed the RNGs of the ``spaces`` to ensure reproducible sampling. z7 does not inherit from `gymnasium.Space`. Actual Type: N)tuplespaces isinstancertypesuper__init__)selfr seedspace __class__s P/home/james-whalen/.local/lib/python3.13/site-packages/gymnasium/spaces/tuple.pyrTuple.__init__sjFm [[Eu ^OPTUZP[}] ^! tT*c:[SUR55$)zDChecks whether this space can be flattened to a :class:`spaces.Box`.c38# UHoRv M g7fN)is_np_flattenable.0rs r *Tuple.is_np_flattenable..1sD u** s)allr rs rrTuple.is_np_flattenable.sD DDDrc>Uc[SUR55$[U[5(a[TU]U5 UR R[R"[R5R[UR5S9n[S[URU555$[U[[45(at[U5[UR5:wa-[S[U5S[UR535e[S[XR555$[!S[#U535e)aSeed the PRNG of this space and all subspaces. Depending on the type of seed, the subspaces will be seeded differently * ``None`` - All the subspaces will use a random initial seed * ``Int`` - The integer is used to seed the :class:`Tuple` space that is used to generate seed values for each of the subspaces. Warning, this does not guarantee unique seeds for all the subspaces. * ``List`` / ``Tuple`` - Values used to seed the subspaces. This allows the seeding of multiple composite subspaces ``[42, 54, ...]``. Args: seed: An optional list of ints or int to seed the (sub-)spaces. Returns: A tuple of the seed values for all subspaces c3B# UHoRS5v M g7frrrs rrTuple.seed..CsC{eD)){s)sizec3Z# UH!upUR[U55v M# g7fr)rint)rsubspacesubseeds rrr&Is*)C%H c'l++)Cs)+z\Expects that the subspaces of seeds equals the number of subspaces. Actual length of seeds: z, length of subspaces: c3H# UHupURU5v M g7frr%)rr+rs rrr&Ss":P 7##:P "z;Expected seed type: list, tuple, int or None, actual type: )r r r r)rr np_randomintegersnpiinfoint32maxlenziplist ValueError TypeErrorr)rrsubseedsrs rr Tuple.seed3sW <Ct{{CC C c " " GL ~~.."&&S-=/H),T[[()C udm , ,4yC ,, rsvw{s|r}~UVYZ^ZeZeVfUgh:=dKK:P MdSWj\Z rcUbUb[SUSU35eUb[U[5(dS[U535e[ U5[ UR 5:Xd)S[ UR 5S[ U535e[S[ UR U555$Ub[U[5(dS[U535e[ U5[ UR 5:Xd)S[ UR 5S[ U535e[S [ UR U555$[S UR 55$) aGenerates a single random sample inside this space. This method draws independent samples from the subspaces. Args: mask: An optional tuple of optional masks for each of the subspace's samples, expects the same number of masks as spaces probability: An optional tuple of optional probability masks for each of the subspace's samples, expects the same number of probability masks as spaces Returns: Tuple of the subspace's samples zIOnly one of `mask` or `probability` can be provided, actual values: mask=z, probability=z2Expected type of `mask` to be tuple, actual type: z Expected length of `mask` to be z, actual length: c3D# UHupURUS9v M g7f))maskNsample)rr space_masks rrTuple.sample..ys%)?%E * -)? z9Expected type of `probability` to be tuple, actual type: z'Expected length of `probability` to be c3D# UHupURUS9v M g7f)) probabilityNr>)rrspace_probabilitys rrrAs&0M,E ): ;0MrBc3@# UHoR5v M g7frr>rs rrrAsA[E[s)r7r r rr4r r5)rr=rDs rr? Tuple.sample[s$   7[\`[aaop{o|}  e QCDJ<P Qt9 ! a1#dkk2B1CCTUXY]U^T_` a),T[[$)?   $U _J4P[K\J]^ _{#s ( o8T[[9I8JJ[\_`k\l[mn o03DKK0M  AT[[AA Arc,[U[[R45(a [ U5n[U[5=(aN [ U5[ UR 5:H=(a& [S[UR U555$)z?Return boolean specifying if x is a valid member of this space.c3H# UHupURU5v M g7fr)contains)rrparts rr!Tuple.contains..s R>Q]eENN4((>Qr-) r r6r0ndarrayr r4r r r5)rxs rrJTuple.containssl a$ + , ,aA q%  SA#dkk** SRc$++q>QRR rc SSRURVs/sHn[U5PM sn5-S-$s snf)z,Gives a string representation of this space.zTuple(z, ))joinr str)rss r__repr__Tuple.__repr__s5$))T[[$A[SV[$ABBSHH$As< c [UR5VVVs/sH)up#URUVs/sHoDUPM sn5PM+ snnn$s snfs snnnf)zCConvert a batch of samples from this space to a JSONable data type.) enumerater to_jsonablersample_nirr?s rrYTuple.to_jsonablesS&dkk2 2   x@xVayx@ A2  @ sAA AAc [[UR5VVs/sHup#URX5PM snn6Vs/sHnUPM sn$s snnfs snf)zCConvert a JSONable data type to a batch of samples from this space.)r5rXr from_jsonablerZs rr_Tuple.from_jsonablesl%.dkk$:$:'' 4$:     s A  Ac URU$)z%Get the subspace at specific `index`.r )rindexs r __getitem__Tuple.__getitem__s{{5!!rc,[UR5$)zGGet the number of subspaces that are involved in the cartesian product.)r4r r!s r__len__ Tuple.__len__s4;;rcb[U[5=(a URUR:H$)z7Check whether ``other`` is equivalent to this instance.)r rr )rothers r__eq__ Tuple.__eq__s!%'GDKK5<<,GGrrbr)r zIterable[Space[Any]]rz7int | typing.Sequence[int] | np.random.Generator | None)rz!int | typing.Sequence[int] | Nonereturnztuple[int, ...])NN)r=tuple[Any | None, ...] | NonerDrnrmztuple[Any, ...])rNrrmbool)rmrS)r[z typing.Sequence[tuple[Any, ...]]rmlist[list[Any]])r[rprmzlist[tuple[Any, ...]])rcr)rmz Space[Any])rmr))rjrrmro)__name__ __module__ __qualname____firstlineno____doc__rpropertyrrr?rJrUrYr_rdrgrk__static_attributes__ __classcell__)rs@rrrs IM+$+F++(EE&&T/3590B+0B30B  0Bd  I 8    " HHrr.)ru __future__rtypingcollections.abcrrnumpyr0gymnasium.spaces.spacerr SequencerrrrsBV" $(nHE%S/ "FOOC$8nHr