class_docstr: Softmax policy that consists of FC layers and rectifiers
class_docstr_tok: ["Softmax","policy","that","consists","of","FC","layers","and","rectifiers"]
code: def __init__(
      self,
      n_input_channels,
      n_actions,
      n_hidden_layers=0,
      n_hidden_channels=None,
      beta=1.0,
      nonlinearity=F.relu,
      last_wscale=1.0,
      min_prob=0.0,
  ):
      self.n_input_channels = n_input_channels
      self.n_actions = n_actions
      self.n_hidden_layers = n_hidden_layers
      self.n_hidden_channels = n_hidden_channels
      self.beta = beta
  
      super().__init__(
          model=MLP(
              n_input_channels,
              n_actions,
              (n_hidden_channels,) * n_hidden_layers,
              nonlinearity=nonlinearity,
              last_wscale=last_wscale,
          ),
          beta=self.beta,
          min_prob=min_prob,
      )
  
file_path: chainerrl/chainerrl/policies/softmax_policy.py
imports: from logging import getLogger
  import chainer
  from chainer import functions
  from chainerrl import distribution
  from chainerrl.links.mlp import MLP
  from chainerrl.policy import Policy
label_desc: Use image node_id 1 to create a new FCSoftmaxPolicy object from inherited base classes: SoftmaxPolicy with example: obj = FCSoftmaxPolicy(n_input_channels, n_actions, n_hidden_layers, n_hidden_channels, beta, nonlinearity, last_wscale, min_prob)