def run(credentials, user, password, task_name):
"""
Run the algorithm for the given task as participant.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:param task_name: training task to be performed
:type task_name: `str`
"""
context = fflapi.Context.from_credentials_file(credentials, user, password)
user = fflapi.User(context, task_name=task_name)
with user:
import json
task_definition = json.loads(user.task_info()['definition'])
participant = fflapi.Participant(context,
task_name=task_name,
download_models=False)
import sys
sys.path.append("../fl_algorithm")
alg_class = get_class(task_definition['participant'])
algorithm = alg_class(task_definition, participant)
try:
algorithm.start()
except Exception as e:
LOGGER.error(str(e))
LOGGER.info('Completed training')
def test_get_tasks(self):
context = fflapi.Context.from_credentials_file(self.credentials)
user = fflapi.User(context)
with user:
result = user.get_tasks()
for r in result:
LOGGER.info(f"{r['task_name']}")
def get_tasks(credentials):
"""
Get a list of all the tasks.
:param credentials: json file containing credentials.
:type credentials: `str`
:return: list of all the tasks, each of which is a dictionary
:rtype: `list`
"""
context = fflapi.Context.from_credentials_file(credentials)
with fflapi.User(context) as ffl:
tasks = ffl.get_tasks()
return tasks
def get_user_assignments(credentials, user, password):
"""
Retrieve a list of all the tasks the user is participating in.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:return: list of all the tasks the user is participating in
:rtype: `list`
"""
context = fflapi.Context.from_credentials_file(credentials, user, password)
user = fflapi.User(context)
with user:
return user.messenger.user_assignments()
def join_task(credentials, user, password, task_name):
"""
Join a Federated ML task.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:param task_name: name of the task (must be unique)
:type task_name: `str`
"""
context = fflapi.Context.from_credentials_file(credentials, user, password)
user = fflapi.User(context, task_name=task_name)
with user:
user.join_task()
def run(credentials, user, password, task_name):
"""
Run the algorithm for the given task as aggregator.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:param task_name: training task to be performed
:type task_name: `str`
"""
context = fflapi.Context.from_credentials_file(credentials, user, password)
user = fflapi.User(context, task_name=task_name)
with user:
import json
task_definition = json.loads(user.task_info()['definition'])
aggregator = fflapi.Aggregator(context,
task_name=task_name,
download_models=False)
import sys
sys.path.append("../fl_algorithm")
alg_class = get_class(task_definition['aggregator'])
algorithm = alg_class(task_definition, aggregator)
model = None
try:
model = algorithm.start()
except Exception as e:
traceback.print_exc()
LOGGER.error(str(e))
LOGGER.info('Dispatch final model to participants...')
with aggregator:
aggregator.stop_task(model)
LOGGER.info('Completed training')
def get_task_participants(credentials, user, password, task_name):
"""
Retrieve a list with details of all the task participants.
If called by a participant different from the task creator, the returned list will be empty.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:param task_name: name of the task (must be unique)
:type task_name: `str`
:return: list with the details of all the task participants
:rtype: `list`
"""
context = fflapi.Context.from_credentials_file(credentials, user, password)
user = fflapi.User(context)
with user:
return user.messenger.task_assignments(task_name)
def create_task(credentials, user, password, task_name, task_definition):
"""
Create a Federated ML task.
:param credentials: json file containing credentials.
:type credentials: `str`
:param user: user name for authentication as task creator
:type user: `str`
:param password: password for authentication as task creator
:type password: `str`
:param task_name: name of the task (must be unique)
:type task_name: `str`
:param task_definition: definition of the task
:type task_definition: `dict`
"""
creator_context = fflapi.Context.from_credentials_file(
credentials, user, password)
creator = fflapi.User(creator_context, task_name=task_name)
topology = fflapi.Topology.star
with creator:
result = creator.create_task(topology, task_definition)
return result