h\SSKJrJrJrJrJr SSKrSSKr SSKJ r SSK J r \"S\ \ R5r"SS\R \\5r"SS \\ R5r"S S \\ R5r"S S \\ R5r"SS\R 5rg))AnyGenericOptionalTypeVarUnionN)spaces) GymStepReturnTc ^\rSrSrSS\\S\\RS\4SjjrSSS.S\\S \\ S \ \ \ 44U4S jjjr S \ S \ \ \ \\\ \\444S jrSSjrS \ S \ 4SjrSS\S S4SjjrSrU=r$) IdentityEnv Ndimspace ep_lengthcUcUcSn[R"U5nO UbS5eU=UlUlX0lSUlSUlUR5 g)a Identity environment for testing purposes :param dim: the size of the action and observation dimension you want to learn. Provide at most one of ``dim`` and ``space``. If both are None, then initialization proceeds with ``dim=1`` and ``space=None``. :param space: the action and observation space. Provide at most one of ``dim`` and ``space``. :param ep_length: the length of each episode in timesteps NzBarguments for both 'dim' and 'space' provided: at most one allowedr)rDiscrete action_spaceobservation_spacer current_step num_resetsreset)selfrrrs d/home/james-whalen/.local/lib/python3.13/site-packages/stable_baselines3/common/envs/identity_env.py__init__IdentityEnv.__init__ s^ ={OOC(E; d d d;5::D2" seedoptionsr r!returnc>Ub [TU]US9 SUlU=RS- slUR 5 UR 04$)Nr rr)superrrr_choose_next_statestaterr r! __class__s rrIdentityEnv.reset%sG   GMtM $ 1 !zz2~ractioncURU5nUR5 U=RS- slSnURUR:nURX#U04$NrF _get_rewardr&rrr'rr+reward terminated truncateds rstepIdentityEnv.step-[!!&) ! Q %%7 zz6y"<[R"XS[RS9n[TU]XES9 X0lg)z Identity environment for testing purposes :param low: the lower bound of the box dim :param high: the upper bound of the box dim :param eps: the epsilon bound for correct value :param ep_length: the length of each episode in timesteps )rr^r_shapedtyperrN)rBoxr?float32r%rr`)rr^r_r`rrr)s rrIdentityEnvBox.__init__@s0 sTL 9:rr+r"cURU5nUR5 U=RS- slSnURUR:nURX#U04$r-r.r0s rr4IdentityEnvBox.stepMr6rcURUR- Us=::aURUR-::aS$ S$r<)r'r`rAs rr/IdentityEnvBox._get_rewardUs7zzDHH,RDJJ[R"X/5n[TU] X#S9 gz Identity environment for testing purposes :param dim: the size of the dimensions you want to learn :param ep_length: the length of each episode in timesteps reN)r MultiDiscreter%rrrrrr)s rr!IdentityEnvMultiDiscrete.__init__Zs'$$cZ0 9:rrErrJrMrNrOrPrQrrXrYrZs@rroroY";C;;d;;rroc<^\rSrSrSS\S\SS4U4SjjjrSrU=r$) IdentityEnvMultiBinaryerrr"NcL>[R"U5n[TU] X#S9 grr)r MultiBinaryr%rrts rrIdentityEnvMultiBinary.__init__fs%""3' 9:rrErvrwrZs@rrzrzerxrrzc^\rSrSrSrSS\S\S\S\S\S\S S 4S jjrS S S .S \\S\\ S \ \ R\ 44U4Sjjjr S\\ R\4S \4SjrSS\S S 4SjjrSrU=r$) FakeImageEnvqaw Fake image environment for testing purposes, it mimics Atari games. :param action_dim: Number of discrete actions :param screen_height: Height of the image :param screen_width: Width of the image :param n_channels: Number of color channels :param discrete: Create discrete action space instead of continuous :param channel_first: Put channels on first axis instead of last action_dim screen_height screen_width n_channelsdiscrete channel_firstr"NcTX#U4UlU(a XBU4Ul[R"SSUR[RS9UlU(a[R "U5UlO*[R"SSS[RS9UlSUl SUl g)Nrrbrr) ) observation_shaperrfr?uint8rrrrgrr)rrrrrrrs rrFakeImageEnv.__init__}s#0z!J &0%ND "!'4CYCYacaiai!j  & ;D  & rRZZ XD rrr r!cj>Ub [TU]US9 SUlURR 504$)Nr$r)r%rrrr9r(s rrFakeImageEnv.resets9   GMtM $%%,,.22rr+cSnU=RS- slSnURUR:nURR5X#U04$)Nr>rF)rrrr9r0s rr4FakeImageEnv.stepsO Q %%7 %%,,.IrQQrrCcgr8rErFs rrGFakeImageEnv.renderrIr)rrrrr)TrrTFrK)rMrNrOrP__doc__rQrVrrrSrTr?rmrrr r4rWrGrXrYrZs@rrrqs #      (.2T3Xc]3HTN3V[\^\f\fhl\lVm33 R5S1RmR 3 T  rr)typingrrrrr gymnasiumgymnumpyr?r%stable_baselines3.common.type_aliasesr rQrmr Envr r\rorzrrErrrs99? Cbjj!0 #''71:0 f\[,\4 ;{2::6 ; ;[4 ;. 377. r