o $i!@sddlmZddlmZddlmZddlmZddlm Z ddl m Z e \Z Z eGdddZeGd d d ZeGd d d ZeGd ddZeGdddZdS)) PolicyState) SampleBatch) TorchPolicy) OldAPIStack)try_import_torch)PiecewiseSchedulecs*eZdZdZdddZfddZZS)LearningRateSchedulez9Mixin for TorchPolicy that adds a learning rate schedule.NcCs~d|_d|_|dur||_nt||dddd|_|jd|_|dur*||_dSt||dddd|_|jd|_dS)N outside_value frameworkr) _lr_schedule _lr2_schedulecur_lrrvaluecur_lr2)selflr lr_schedulelr2 lr2_schedulerZ/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/ray/rllib/policy/torch_mixins.py__init__s zLearningRateSchedule.__init__cst||jr#|j|d|_|jD] }|jD]}|j|d<qq|jrHt|jdks/J|j|d|_ |jd}|jD] }|j |d<q@dSdS)Ntimestepr) superon_global_var_updater rr _optimizers param_groupsrlenr)r global_varsoptp __class__rrr#s       z)LearningRateSchedule.on_global_var_update)NN__name__ __module__ __qualname____doc__rr __classcell__rrr%rr s rcs(eZdZdZddZfddZZS)EntropyCoeffSchedulez4Mixin for TorchPolicy that adds entropy coeff decay.cCsjd|_|dur ||_dSt|trt||dddd|_ntd|g|dggddd|_|jd|_dS)Nr r r)_entropy_coeff_schedule entropy_coeff isinstancelistrr)rr0entropy_coeff_schedulerrrr6s    zEntropyCoeffSchedule.__init__cs4tt|||jdur|j|d|_dSdS)Nr)rr-rr/rr0)rr"r%rrrMs   z)EntropyCoeffSchedule.on_global_var_updater'rrr%rr-2sr-csLeZdZdZddZddZdeffdd Zd edd ffd d ZZ S) KLCoeffMixinzAssigns the `update_kl()` method to a TorchPolicy. This is used by Algorithms to update the KL coefficient after each learning step based on `config.kl_target` and the measured KL value (from the train_batch). cCs|d|_|d|_dS)Nkl_coeff kl_target)r5r6)rconfigrrrr^s zKLCoeffMixin.__init__cCsD|d|jkr|jd9_|jS|d|jkr|jd9_|jS)Ng@g?g?)r6r5)r sampled_klrrr update_klds zKLCoeffMixin.update_klreturncst}|j|d<|S)Ncurrent_kl_coeff)r get_stater5rstater%rrr<ms  zKLCoeffMixin.get_stater>Ncs$|d|jd|_t|dS)Nr;r5)popr7r5r set_stater=r%rrr@sszKLCoeffMixin.set_state) r(r)r*r+rr9rr<r@r,rrr%rr4Us  r4c@s eZdZdZddZddZdS)ValueNetworkMixinaAssigns the `_value()` method to a TorchPolicy. This way, Policy can call `_value()` to get the current VF estimate on a single(!) observation (as done in `postprocess_trajectory_fn`). Note: When doing this, an actual forward pass is being performed. This is different from only calling `model.value_function()`, where the result of the most recent forward pass is being used to return an already calculated tensor. cs4|ds |drfdd}ndd}|_dS)Nuse_gaevtracecs2t|}|}|\}}jdS)Nr)r_lazy_tensor_dictmodelvalue_functionitem) input_dict model_out_rrrrs z)ValueNetworkMixin.__init__..valuec_sdS)Nr.r)argskwargsrrrrs)get_value)rr7rrrKrrs zValueNetworkMixin.__init__cCstj|iS)aDefines extra fetches per action computation. Args: input_dict (Dict[str, TensorType]): The input dict used for the action computing forward pass. state_batches (List[TensorType]): List of state tensors (empty for non-RNNs). model (ModelV2): The Model object of the Policy. action_dist: The instantiated distribution object, resulting from the model's outputs and the given distribution class. Returns: Dict[str, TensorType]: Dict with extra tf fetches to perform per action computation. )rVF_PREDSrF)rrH state_batchesrE action_distrrrextra_action_outs z"ValueNetworkMixin.extra_action_outN)r(r)r*r+rrSrrrrrAzs rAc@s*eZdZdZddZd ddZddZdS) TargetNetworkMixinaMixin class adding a method for (soft) target net(s) synchronizations. - Adds the `update_target` method to the policy. Calling `update_target` updates all target Q-networks' weights from their respective "main" Q-networks, based on tau (smooth, partial updating). cCs|jdd}|j|ddS)Ntau?)rU)r7rN update_target)rrUrrrrszTargetNetworkMixin.__init__Ncshp|jdd|jtt|j}fdd|D|jD]}| q*dS)NrUrVcs*i|]\}}||d|qS)rr).0kvmodel_state_dictrUrr sz4TargetNetworkMixin.update_target..) r7rNrE state_dictnextiter target_modelsvaluesitemsload_state_dict)rrUtarget_state_dicttargetrr[rrWs   z TargetNetworkMixin.update_targetcCst|||dSN)r set_weightsrW)rweightsrrrrhs  zTargetNetworkMixin.set_weightsrg)r(r)r*r+rrWrhrrrrrTs   rTN)ray.rllib.policy.policyrray.rllib.policy.sample_batchrray.rllib.policy.torch_policyrray.rllib.utils.annotationsrray.rllib.utils.frameworkrray.rllib.utils.schedulesrtorchnnrr-r4rArTrrrrs"      &"$;