class_docstr: Unit tests for QLearning.
class_docstr_tok: ["Unit","tests","for","QLearning","."]
code: def _setup_parameters(self, parameters):
      parameters.q_representation = "dqn"
      parameters.hidden_layers = "[2]"
      parameters.initial_epsilon = 0.1
      parameters.epsilon_decay_step_count = 9
      parameters.epsilon_minimum = 0.01
      parameters.initial_eta = 0.1
      parameters.eta_decay_step_count = 9
      parameters.eta_minimum = 0.01
      parameters.momentum = 0.95
      parameters.gradient_clipping_threshold = 10
      parameters.q_update_frequency = 2
      parameters.gamma = 0.9
      parameters.double_q_learning = False
      parameters.replay_start_size = 0
      parameters.replay_memory_capacity = 100
      parameters.use_prioritized_replay = False
      parameters.priority_alpha = 2
      parameters.priority_beta = 2
      parameters.priority_epsilon = 0.1
      parameters.preprocessing = ""
      parameters.use_error_clipping = False
      parameters.replays_per_update = 1
  
imports: import unittest
  import cntk.contrib.deeprl.tests.spaces
  import numpy
  from cntk.contrib.deeprl.agent.qlearning import QLearning
  from cntk.contrib.deeprl.agent.shared.cntk_utils import huber_loss
  from cntk.contrib.deeprl.agent.shared.replay_memory import _Transition
  from cntk.layers import Dense
  from cntk.losses import squared_error
  from cntk.ops import input_variable
label_desc: Use image node_id 14 for calling the QLearningTest obj's underlying member method code with example usage: obj._setup_parameters(parameters) without return types