text: # Copyright 2017 reinforce.io. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ==============================================================================
  
  from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import division
  
  import unittest
  
  from tensorforce.tests.base_test import BaseTest
  from tensorforce.agents import DQNAgent
  from tensorforce.environments.minimal_test import MinimalTest
  
  
  class TestDQNMemories(BaseTest, unittest.TestCase):
  
      agent = DQNAgent
      deterministic = True
  
      def test_replay(self):
          environment = MinimalTest(specification={'int': ()})
          network_spec = [
              dict(type='dense', size=32),
              dict(type='dense', size=32)
          ]
          config = dict(
              memory=dict(
                  type='replay',
                  capacity=1000
              ),
              repeat_update=4,
              batch_size=32,
              first_update=64,
              target_sync_frequency=10
          )
  
          self.base_test_pass(
              name='replay',
              environment=environment,
              network_spec=network_spec,
              **config
          )
  
      def test_prioritized_replay(self):
          environment = MinimalTest(specification={'int': ()})
          network_spec = [
              dict(type='dense', size=32),
              dict(type='dense', size=32)
          ]
  
          config = dict(
              memory=dict(
                  type='prioritized_replay',
                  capacity=1000
              ),
              repeat_update=4,
              batch_size=32,
              first_update=64,
              target_sync_frequency=10
          )
  
          self.base_test_pass(
              name='prioritized-replay',
              environment=environment,
              network_spec=network_spec,
              **config
          )
  
      def test_naive_prioritized_replay(self):
          environment = MinimalTest(specification={'int': ()})
          network_spec = [
              dict(type='dense', size=32),
              dict(type='dense', size=32)
          ]
          config = dict(
              memory=dict(
                  type='naive_prioritized_replay',
                  capacity=1000
              ),
              repeat_update=4,
              batch_size=32,
              first_update=64,
              target_sync_frequency=10
          )
  
          self.base_test_pass(
              name='naive-prioritized-replay',
              environment=environment,
              network_spec=network_spec,
              **config
          )
  