def main():
"""
Main entry point.
"""
try:
cmdline = args_parse()
context = utils.platform(cmdline.platform, cmdline.credentials,
cmdline.user, cmdline.password)
# create new machine learning task
task_definition = {
"aggregator": "neural_network.Aggregator",
"participant": "neural_network.Participant",
"quorum": 2,
"round": 5,
"epoch": 2,
"batch_size": 256,
"learning_rate": 0.001,
"training_size": 10000,
"test_size": 1000,
}
result = create_task(context, cmdline.task_name, task_definition)
LOGGER.debug(result)
LOGGER.info('Task created.')
except Exception as err:
LOGGER.error('Error: %s', err)
raise err
def main():
"""
Main entry point.
"""
try:
cmdline = args_parse()
context = utils.platform(cmdline.platform, cmdline.credentials)
create_user(context, cmdline.user, cmdline.password, cmdline.org)
LOGGER.info('User %s created', cmdline.user)
except Exception as err:
LOGGER.error('Error: %s', err)
def main():
"""
Main entry point.
"""
try:
cmdline = args_parse()
context = utils.platform(cmdline.platform, cmdline.credentials, cmdline.user, cmdline.password)
run(context, cmdline.task_name)
except Exception as err:
LOGGER.error('Error: %s', err)
raise err
def main():
"""
Main entry point.
"""
try:
cmdline = args_parse()
context = utils.platform(cmdline.platform, cmdline.credentials,
cmdline.user, cmdline.password)
tasks = get_tasks(context)
for task in tasks:
LOGGER.info(f"{task['task_name']} - {task['status']}")
except Exception as err:
LOGGER.error('Error: %s', err)