niSrSSKJr SSKJr SSKJr SSKrSSKrSSKrSSKJ s J r SSKJr SSKJr SS KJr S rS rS rS r\S:Xa\ R.R0R2r\ R.R0R5SSS5 \ R.R0R5S\R R75R9S5S5 \ R.R0R5SSS5 \ R.R0R;SSS5 \ R.R=5 gg!\ a SSK r GN0f=f)zScript to train a batch reinforcement learning algorithm. Command line: python3 -m agents.scripts.train --logdir=/path/to/logdir --config=pendulum )absolute_import)division)print_functionN)tools)configs)utilityc[UR[5(a![R"UR5nOUR5nUR (a)[ RRXR 5n[ RRU5n[ RRU5n[ RRU5nU$)zConstructor for an instance of the environment. Args: config: Object providing configurations via attributes. Returns: Wrapped OpenAI Gym environment. ) isinstanceenvstrgymmake max_lengthrwrappers LimitDurationRangeNormalize ClipActionConvertTo32Bit)configr s X/home/james-whalen/.local/lib/python3.13/site-packages/pybullet_envs/agents/train_ppo.py_create_environmentr's C  ((6:: C **,C  .. & &s,=,= >C %%c*# !!#&# %%c*# *c [R"XRURURUR 5nUR SURURURUUUS-SURS0S9 UR SURURURUUUS-SU-URS0S9 U$) aICreate and configure a training loop with training and evaluation phases. Args: graph: Object providing graph elements via attributes. logdir: Log directory for storing checkpoints and summaries. train_steps: Number of training steps per epoch. eval_steps: Number of evaluation steps per epoch. Returns: Loop object. trainNT) report_every log_everycheckpoint_everyfeedeval F) rLoopstep should_log do_report force_reset add_phasedonescoresummary is_training)graphlogdir train_steps eval_stepsloops r _define_loopr2<s FJJ(8(8%//5K\K\ ]$..)&!+"&(($/1..(%?"$z/((%02 +rc#^# [R"5 TRTR-(a[RR S5 [R "S5 [R"U4SjTRU5n[R"UTRT5n[UTRTRTR-TRTR-5n[TR TR- TRTR--5nSSS5 [R""SS9n[R$"SS9nSUR&l[R*"US 9n[R,"XTR5 WR/XW5Hn U v M SSS5 WR15 g!,(df  N=f!,(df  N0=f7f) aaTraining and evaluation entry point yielding scores. Resolves some configuration attributes, creates environments, graph, and training loop. By default, assigns all operations to the CPU. Args: config: Object providing configurations via attributes. env_processes: Whether to step environments in separate processes. Yields: Evaluation scores. z3Number of agents should divide episodes per update.z/cpu:0c>[T5$)N)rrsrtrain..os 1DV1LrN)z.*_temporary/.*)excludeT)allow_soft_placementr5)tfreset_default_graph update_every num_agentsloggingwarndevicer define_batch_envdefine_simulation_graph algorithmr2r.r eval_episodesintsteps define_saver ConfigProto gpu_options allow_growthSessioninitialize_variablesrunclose) r env_processes batch_envr-r1 total_stepssaver sess_configsessr*s ` rrr^s 6,,,JJOOIJ yy(()LfN_N_)68I  + +Iv7G7G PE v}}f.A.AFDUDU.U,,v/@/@@ BDfllV%8%88**V-A-AACDK    '< =%D9+)-+& zz%   fmm<${3 k4& //#&%s8A)H,C G$7AH ?G5 H$ G2.H5 H?Hc [R"5 [R(d [ S5e[R =(aw [ RR[ RR[R SR[R[R555n[R"U5n['U[R(5H1n[*R,R/SRU55 M3 g![aP [R"[!["[R5"55n[R$"X!5nNf=f)z4Create or load configuration and launch the trainer.z!You must specify a configuration.z{}-{}z Score {}.N)r set_up_loggingFLAGSrKeyErrorr.ospath expanduserjoinformat timestamp load_configIOErrorrAttrDictgetattrr save_configrrOr:r>info)_r.rr*s rmainrfs   6 77 << QBGG..ggll5<<!NOQ&1   (FVU001eJJOOK&&u-.2 1 ^^GGU\\:< =F   0F1sD++AFF__main__r.zBase directory to store logs.r^z %Y%m%dT%H%M%SzSub directory to store logs.rzConfiguration to execute.rOTz>Step environments in separate processes to circumvent the GIL.)__doc__ __future__rrrdatetimerYrtensorflow.compat.v1compatv1r: Exception tensorflowrrr rr2rrf__name__appflagsrW DEFINE_stringnowstrftimeDEFINE_booleanrMrrrys'% ## *D!H /  z &&,,  %&&,,Xt-LM&&,,[%..224==oN;=&&,,Xt-HI&&,,ot^`&&**,gs E EE