def __init__(self, name: Optional[str] = None):
"""Creates an instance of `Network`.
Args:
name: A string representing the name of the network.
"""
self._log = logger.get_logger(self.__class__.__name__)
self._config_handler = KatherineApplication.get_application_config()
self._serializer = KatherineApplication.get_application_factory(
).build_model_serializer()
self._name = name or None
self._load_configuration()
def __init__(self):
"""
Default constructor.
"""
self._log = logger.get_logger(self.__class__.__name__)
self._config_handler = KatherineApplication.get_application_config()
if not self._config_handler:
raise ValueError("No config specified.")
self._game = KatherineApplication.get_application_factory().build_game()
self._agent = KatherineApplication.get_application_factory().build_agent()
self._metrics = KatherineApplication.get_application_factory().build_metrics_tracer()
self._load_configuration()
def __init__(self):
"""
Default constructor.
"""
self._load_configuration()
self._work_directory = fileio.build_models_work_directory(WORKING_DIRECTORY_PREFIX)
self._storage_driver = KatherineApplication.get_application_factory().build_model_storage_driver()
def _build_memory_access(self) -> None:
"""
Helper function for building readonly memory.
"""
if self._memory_access is None:
self._memory_access = KatherineApplication.get_application_factory(
).build_memory_access()
self._memory_access.init(self._replay_memory)
def __init__(self):
"""
Default constructor.
"""
self._config_handler = KatherineApplication.get_application_config()
if not self._config_handler:
raise ValueError("No config_handler specified")
self._log = logger.get_logger(self.__class__.__name__)
def _load_configuration() -> Collection[Tuple]:
"""
Loads the server configurations.
:return:
a list of tuples with server configs
"""
return KatherineApplication.get_application_config(
).get_config_property(KatConfigurationProperty.CLUSTER_INFO,
KatConfigurationProperty.CLUSTER_INFO.prop_type)
def _load_configuration(self):
"""
Loads necessary configurations.
"""
self._config_handler = KatherineApplication.get_application_config()
if not self._config_handler:
raise ValueError("No configuration handler specified.")
self._train_batch_size = self._config_handler.get_config_property(
KatConfigurationProperty.TRAIN_BATCH_SIZE,
KatConfigurationProperty.TRAIN_BATCH_SIZE.prop_type)
self._distributed_learning_enabled = self._config_handler.get_config_property(
AgentConfigurationProperty.DISTRIBUTED_LEARNING_ENABLED,
AgentConfigurationProperty.DISTRIBUTED_LEARNING_ENABLED.prop_type)
self._convert_to_monochrome = self._config_handler.get_config_property(
AgentConfigurationProperty.CONVERT_TO_MONOCHROME,
AgentConfigurationProperty.CONVERT_TO_MONOCHROME.prop_type)
self._screen_channels = self._config_handler.get_config_property(
AgentConfigurationProperty.SCREEN_CHANNELS,
AgentConfigurationProperty.SCREEN_CHANNELS.prop_type)
self._frame_stacking_enabled = self._config_handler.get_config_property(
AgentConfigurationProperty.FRAME_STACKING_ENABLED,
AgentConfigurationProperty.FRAME_STACKING_ENABLED.prop_type)
self._number_of_stacked_frames = self._config_handler.get_config_property(
AgentConfigurationProperty.NUMBER_OF_STACKED_FRAMES,
AgentConfigurationProperty.NUMBER_OF_STACKED_FRAMES.prop_type)
self._screen_size = (
self._config_handler.get_config_property(
AgentConfigurationProperty.SCREEN_HEIGHT,
AgentConfigurationProperty.SCREEN_HEIGHT.prop_type),
self._config_handler.get_config_property(
AgentConfigurationProperty.SCREEN_WEIGHT,
AgentConfigurationProperty.SCREEN_WEIGHT.prop_type))
self._input_observation_name = self._config_handler.get_config_property(
AgentConfigurationProperty.INPUT_OBSERVATION_NAME,
AgentConfigurationProperty.INPUT_OBSERVATION_NAME.prop_type)
self._initial_epsilon = self._config_handler.get_config_property(
AgentConfigurationProperty.INITIAL_EXPLORATION_RATE,
AgentConfigurationProperty.INITIAL_EXPLORATION_RATE.prop_type)
self._final_epsilon = self._config_handler.get_config_property(
AgentConfigurationProperty.FINAL_EXPLORATION_RATE,
AgentConfigurationProperty.FINAL_EXPLORATION_RATE.prop_type)
self._constant_exploration = self._config_handler.get_config_property(
AgentConfigurationProperty.CONSTANT_EXPLORATION_PERCENTAGE,
AgentConfigurationProperty.CONSTANT_EXPLORATION_PERCENTAGE.
prop_type)
self._decaying_exploration = self._config_handler.get_config_property(
AgentConfigurationProperty.DECAYING_EXPLORATION_PERCENTAGE,
AgentConfigurationProperty.DECAYING_EXPLORATION_PERCENTAGE.
prop_type)
self._max_episodes = self._config_handler.get_config_property(
KatConfigurationProperty.MAX_EPISODES,
KatConfigurationProperty.MAX_EPISODES.prop_type)
self._max_observe_episodes = self._config_handler.get_config_property(
AgentConfigurationProperty.MAX_OBSERVE_EPISODES,
AgentConfigurationProperty.MAX_OBSERVE_EPISODES.prop_type)
def _load_configuration(self) -> None:
"""
Loads the configuration.
"""
config_handler = KatherineApplication.get_application_config()
self._is_model_persistence_enabled = config_handler.get_config_property(
ModelSerializerProperty.MODEL_PERSISTENCE_ENABLED,
ModelSerializerProperty.MODEL_PERSISTENCE_ENABLED.prop_type)
self._is_checkpoints_enabled = config_handler.get_config_property(
ModelSerializerProperty.MODEL_CHECKPOINTS_ENABLED,
ModelSerializerProperty.MODEL_CHECKPOINTS_ENABLED.prop_type)
def __init__(self):
"""
Default constructor.
"""
self._log = logger.get_logger(self.__class__.__name__)
config_handler = KatherineApplication.get_application_config()
self.enabled_metrics = config_handler.get_config_property(
TensorBoardConfigurationProperty.ENABLED_NETWORK_METRICS,
TensorBoardConfigurationProperty.ENABLED_NETWORK_METRICS.prop_type)
self.is_profiler_enabled = config_handler.get_config_property(
TensorBoardConfigurationProperty.GPU_PROFILER_ENABLED,
TensorBoardConfigurationProperty.GPU_PROFILER_ENABLED.prop_type)
self.work_directory = fileio.build_metrics_work_directory(WORKING_DIRECTORY_PREFIX)
self.initialized = False
def build_global_work_directory() -> str:
"""
Helper function for building the application's global working directory.
base_work_directory/game/agent/run_tag
:returns
the global work directory path (relative path)
"""
base_work_directory = KatherineApplication.get_application_config(
).get_config_property(KatConfigurationProperty.WORK_DIRECTORY,
KatConfigurationProperty.WORK_DIRECTORY.prop_type)
agent_name = KatherineApplication.get_application_config(
).get_config_property(KatConfigurationProperty.AGENT_CLASS,
KatConfigurationProperty.AGENT_CLASS.prop_type)
game_name = KatherineApplication.get_application_config(
).get_config_property(KatConfigurationProperty.GAME_CLASS,
KatConfigurationProperty.GAME_CLASS.prop_type)
run_tag = KatherineApplication.get_application_config(
).get_config_property(KatConfigurationProperty.RUN_TAG,
KatConfigurationProperty.RUN_TAG.prop_type)
agent_name = agent_name[agent_name.rindex('.') + 1:]
game_name = game_name[game_name.rindex('.') + 1:]
return os.path.join(base_work_directory, game_name, agent_name, run_tag)
def _build_network(self) -> INetwork:
"""
Helper function for building the network.
:returns
an initialized `INetwork` instance, based on the current configuration
"""
self._build_memory_access()
network = KatherineApplication.get_application_factory().build_network(
)
network.init(
replay_memory_access=self._memory_access,
input_descriptor=self._network_input_spec,
output_descriptor=self._network_output_spec,
is_distribution_enabled=self._distributed_learning_enabled)
return network
def init(self, observation_space_desc: Collection[ITensorDescriptor],
action_space_descriptor: ITensorDescriptor) -> None:
"""
Object initialization.
#see: IAgent.init(observation_space_desc: Collection[ITensorDescriptor],
action_space_desc: ITensorDescriptor)
"""
super(RandomChoiceAgent, self).init(observation_space_desc,
action_space_descriptor)
self._network_input_spec = TensorDescriptor(
self._input_observation_name, self._input_observation_dtype,
self._frame_buffer_output_shape, self._input_observation_type)
self._network_output_spec = TensorDescriptor(
"network_output", self._input_observation_dtype,
self._action_space_desc.get_tensor_shape(), NetworkInputType.NONE)
self._network = KatherineApplication.get_application_factory(
).build_network()
self._network.init(output_descriptor=self._network_output_spec,
input_descriptor=self._network_input_spec)
self._replay_memory = self._build_replay_memory()
def _build_replay_memory(self) -> IReplayMemory:
"""
Helper function for building the replay memory.
:returns
an initialized `IReplayMemory` instance, based on the current configuration
"""
memory_max_size = self._config_handler.get_config_property(
AgentConfigurationProperty.MEMORY_MAX_SIZE,
AgentConfigurationProperty.MEMORY_MAX_SIZE.prop_type)
memory_tensor_spec = \
(TensorDescriptor('s1_states',
self._input_observation_dtype,
(memory_max_size, *self._frame_buffer_output_shape)),
TensorDescriptor('action_ids', self._action_space_desc.get_data_type(), (memory_max_size,)),
TensorDescriptor('s2_states',
self._input_observation_dtype,
(memory_max_size, *self._frame_buffer_output_shape)),
TensorDescriptor('rewards', np.float32, (memory_max_size, )),
TensorDescriptor('terminals', np.bool, (memory_max_size, )))
memory = KatherineApplication.get_application_factory().build_memory()
memory.init(memory_tensor_spec)
return memory
def __init__(self):
"""
Default constructor.
"""
self._config_handler = KatherineApplication.get_application_config()