def init(self):
"""
Init method, initialize member variables and other program parts.
:return: successful: (Boolean) Was the execution successful?
"""
print("Controller: Starting init() ...")
self.__logger = SLoggerHandler().getLogger(LoggerNames.CONTROLLER_C)
self.__logger.info("Loading config ...", "Controller:init")
successful = True
try:
self.__config_provider = ConfigProvider()
self.__config = self.__config_provider.get_config(
self.__controller_config_file_path)
self.__logger.info("Finished loading config.", "Controller:init")
self.__tf_record_handler = TfRecordHandler(
tfrecord_dir="data",
dataset_prepreprocessors=self.
__config["datasetPrePreProcessors"],
num_threads=self.__config["hardware"]["numCPUCores"])
self.__logger.info("Finished init()", "Controller:init")
except:
successful = False
self.__logger.error("Canceled init(). An error accrued!",
"Controller:init")
print(traceback.format_exc())
return successful
def __init__(self, config):
"""
Constructor, initialize member variables.
:param config: (Dictionary) The config of the experiment, containing all model parameters. Refer to the config
csnnReconstructionExperiment.json as an example.
"""
self.__config = config
self.__logger = SLoggerHandler().getLogger(LoggerNames.EXPERIMENT_C)
self.__num_gpus = ConfigProvider().get_config("controllerConfig.json")["hardware"]["numGPUs"]
def init(self):
"""
Init method, initialize member variables and other program parts.
:return: successful: (Boolean) Was the execution successful?
"""
print("Controller: Starting init() ...")
self.__logger = SLoggerHandler().getLogger(LoggerNames.CONTROLLER_C)
self.__logger.info("Loading config ...", "Controller:init")
successful = True
try:
self.__config_provider = ConfigProvider()
self.__config = self.__config_provider.get_config(
self.__controller_config_file_path)
self.__logger.info("Finished loading config.", "Controller:init")
self.__logger.info("Finished init()", "Controller:init")
except:
successful = False
self.__logger.error("Canceled init(). An error accrued!",
"Controller:init")
print(traceback.format_exc())
return successful
def execute(self):
"""
Executes the experiments defined in the given schedule.
If a experiment went wrong, the execution goes on for the next experiment and an execution information is printed
after each experiment.
"""
if self.__schedule["mode"] == "sequential":
self.__finished_experiments = 0
for experiment_name in self.__schedule["experimentsToRun"]:
self.__finished_experiments = self.__finished_experiments + 1
try:
# Dynamically import the experiment class by name.
experiment_module = importlib.import_module(
"Experiment_Component.Experiments." + experiment_name)
# Dynamically load the provider class by name.
# Combined with the above import its like: from Experiment_Component.Experiments.CsnMnistExperiment import CsnMnistExperiment
experiment = getattr(experiment_module, experiment_name)
for config_name in self.__schedule[
"experimentConfigsToRun"][experiment_name]:
try:
config = ConfigProvider().get_config(
"Experiment_Component/ExperimentConfigs/" +
config_name)
experiment(config).execute()
self.__successful_experiments.append(
experiment_name)
self.__logExecutionInfo()
except:
self.__logger.error(
"Cancled experiment " + experiment_name +
" An error accrued:" +
str(traceback.format_exc()),
"ExperimentScheduler:execute")
self.__canceled_experiments.append(experiment_name)
self.__logExecutionInfo()
except:
self.__logger.error(
"Cancled experiment " + experiment_name +
" An error accrued:" + str(traceback.format_exc()),
"ExperimentScheduler:execute")
self.__canceled_experiments.append(experiment_name)
self.__logExecutionInfo()
class Controller:
"""
The controller is the central point of the framework. It takes care of the execution of various programs like
the creation of TfRecord datasets or the execution of experiments via a scheduler.
:Attributes:
__controller_config_file_path: (String) The path to the config for the controller.
__config: (Dictionary) The config of the controller.
__logger: (Logger) The logger for the controller.
__experiment_scheduler: (ExperimentScheduler) The scheduler to handle multiple experiments.
__tf_record_handler: (TfRecordHandler) The handler to create the tf records.
__config_provider: (ConfigProvider) : The provider to request config input.
__experiment_scheduler: (ExperimentScheduler) The scheduler to schedule the experiment execution.
"""
def __init__(self, controller_config_file_path):
"""
Constructor, initialize member variables.
:param controller_config_file_path: (String) String to controllerConfig File.
"""
print("Controller: Starting __init__() ...")
self.__controller_config_file_path = controller_config_file_path
self.__config = None
self.__logger = None
self.__tf_record_handler = None
self.__config_provider = None
self.__experiment_scheduler = None
print("Controller: Finished __init__()")
def init(self):
"""
Init method, initialize member variables and other program parts.
:return: successful: (Boolean) Was the execution successful?
"""
print("Controller: Starting init() ...")
self.__logger = SLoggerHandler().getLogger(LoggerNames.CONTROLLER_C)
self.__logger.info("Loading config ...", "Controller:init")
successful = True
try:
self.__config_provider = ConfigProvider()
self.__config = self.__config_provider.get_config(
self.__controller_config_file_path)
self.__logger.info("Finished loading config.", "Controller:init")
self.__tf_record_handler = TfRecordHandler(
tfrecord_dir="data",
dataset_prepreprocessors=self.
__config["datasetPrePreProcessors"],
num_threads=self.__config["hardware"]["numCPUCores"])
self.__logger.info("Finished init()", "Controller:init")
except:
successful = False
self.__logger.error("Canceled init(). An error accrued!",
"Controller:init")
print(traceback.format_exc())
return successful
def execute(self):
"""
Executes the execution specified in the controllers config.
:return: successful: (Boolean) Was the execution successful??
"""
self.__logger.info("Starting execute() ...", "Controller:execute")
successful = True
if self.__config["executeCreateTfRecordsFromDataset"]:
try:
self.__logger.info(
"Starting executeCreateTfRecordsFromDataset() ...",
"Controller:execute")
self.__tf_record_handler.createTfRecords(
self.__config["datasetsToCreateTfRecords"],
self.__config["datasetTfRecordSplits"])
self.__logger.info(
"Finished executeCreateTfRecordsFromDataset()",
"Controller:execute")
except:
successful = False
self.__logger.error(
"Canceled executeCreateTfRecordsFromDataset(). An error accrued!",
"Controller:execute")
print(traceback.format_exc())
if self.__config["executeExperiments"]:
try:
self.__logger.info("Starting executeExperiments() ...",
"Controller:execute")
# load schedule
experiment_schedule = self.__config_provider.get_config(
"experimentSchedule.json")
self.__experiment_scheduler = ExperimentScheduler(
experiment_schedule)
self.__experiment_scheduler.execute()
self.__logger.info("Finished executeExperiments()",
"Controller:execute")
except:
successful = False
self.__logger.error(
"Canceled executeExperiments(). An error accrued!",
"Controller:execute")
print(traceback.format_exc())
return successful