class_docstr: Continuous deterministic policy.
  
  Args:
      model (chainer.Link):
          Link that is callable and outputs action values.
      model_call (callable or None):
          Callable used instead of model.__call__ if not None
      action_filter (callable or None):
          Callable applied to the outputs of the model if not None
class_docstr_tok: ["Continuous","deterministic","policy",".","Args",":","model","(","chainer.Link",")",":","Link","that","is","callable","and","outputs","action","values",".","model_call","(","callable","or","None",")",":","Callable","used","instead","of","model.__call__","if","not","None","action_filter","(","callable","or","None",")",":","Callable","applied","to","the","outputs","of","the","model","if","not","None"]
code: def __init__(self, model, model_call=None, action_filter=None):
      super().__init__(model=model)
      self.model_call = model_call
      self.action_filter = action_filter
  
imports: from logging import getLogger
  import chainer
  from chainer import functions
  from chainer.initializers import LeCunNormal
  from chainer import links
  from chainerrl import distribution
  from chainerrl.functions.bound_by_tanh import bound_by_tanh
  from chainerrl.links.mlp import MLP
  from chainerrl.links.mlp_bn import MLPBN
  from chainerrl.policy import Policy
  from chainerrl.recurrent import RecurrentChainMixin
label_desc: Use image node_id 1 to create a new ContinuousDeterministicPolicy object from inherited base classes: chainer, Policy, RecurrentChainMixin with example: obj = ContinuousDeterministicPolicy(model, model_call, action_filter)