class_docstr: A model arch similar to FullyConnectedActor, except that the last layer
  is sampled from a Dirichlet distribution
docstr: Get concentration of distribution.
  https://stats.stackexchange.com/questions/244917/what-exactly-is-the-alpha-in-the-dirichlet-distribution
code: def _get_concentration(self, state):
      """
      Get concentration of distribution.
      https://stats.stackexchange.com/questions/244917/what-exactly-is-the-alpha-in-the-dirichlet-distribution
      """
      return self.fc(state.float_features).exp() + self.EPSILON
  
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 3 for calling the DirichletFullyConnectedActor obj's underlying member method code with example usage: obj._get_concentration(state) and returns: unknown