class_docstr: A general model arch for mapping from state to ActorOutput,
  which contains an action tensor and log probabilities (optional).
  
  The model arch is often used to implement the actor in actor-critic algorithms.
code: def __init__(
      self,
      state_dim: int,
      action_dim: int,
      sizes: List[int],
      activations: List[str],
      use_batch_norm: bool = False,
      action_activation: str = "tanh",
      exploration_variance: Optional[float] = None,
  ) -> None:
      super().__init__()
      assert state_dim > 0, "state_dim must be > 0, got {}".format(
          state_dim
      )
      assert action_dim > 0, "action_dim must be > 0, got {}".format(
          action_dim
      )
      self.state_dim = state_dim
      self.action_dim = action_dim
      assert len(sizes) == len(
          activations
      ), "The numbers of sizes and activations must match; got {} vs {}".format(
          len(sizes), len(activations)
      )
      self.action_activation = action_activation
      self.fc = FullyConnectedNetwork(
          [state_dim] + sizes + [action_dim],
          activations + [self.action_activation],
          use_batch_norm=use_batch_norm,
      )
  
      # Gaussian noise for exploration.
      self.exploration_variance = exploration_variance
      if exploration_variance is not None:
          assert exploration_variance > 0
          loc = torch.zeros(action_dim).float()
          scale = torch.ones(action_dim).float() * exploration_variance
          self.noise_dist = Normal(loc=loc, scale=scale)
  
imports: import math
  from typing import List, Optional
  import torch
  from reagent.core import types
  from reagent.core.parameters import CONTINUOUS_TRAINING_ACTION_RANGE
  from reagent.core.tensorboardX import SummaryWriterContext
  from reagent.models.base import ModelBase
  from reagent.models.fully_connected_network import FullyConnectedNetwork
  from torch.distributions import Dirichlet
  from torch.distributions.normal import Normal
label_desc: Use image node_id 1 to create a new FullyConnectedActor object from inherited base classes: ModelBase with example: obj = FullyConnectedActor(state_dim, action_dim, sizes, activations, use_batch_norm, action_activation, exploration_variance)