def __init__(self,
work_mode=WorkModeStrategy.WORKMODE_STANDALONE,
models=None,
data=None,
client_id=0,
client_ip="",
client_port=8081,
server_url="",
curve=False,
local_epoch=5,
concurrent_num=5):
self.work_mode = work_mode
self.data = data
self.client_id = str(client_id)
self.local_epoch = local_epoch
self.concurrent_num = concurrent_num
self.trainer_executor_pool = ThreadPoolExecutor(self.concurrent_num)
self.job_path = JOB_PATH
self.models = models
self.fed_step = {}
self.job_train_strategy = {}
self.client_ip = client_ip
self.client_port = str(client_port)
self.server_url = server_url
self.curve = curve
self.logger = LoggerFactory.getLogger("TrainerController",
logging.INFO)
def __init__(self, job, data, fed_step, client_id, model, curve):
super(TrainStandloneDistillationStrategy,
self).__init__(job, data, fed_step, client_id, model, curve)
self.train_model = self._load_job_model(
job.get_job_id(), job.get_train_model_class_name())
self.logger = LoggerFactory.getLogger(
"TrainStandloneDistillationStrategy", logging.INFO)
def __init__(self, job, data, fed_step, client_ip, client_port, server_url,
client_id, model, curve):
super(TrainMPCDistillationStrategy,
self).__init__(job, data, fed_step, client_id, model, curve)
self.client_ip = client_ip
self.client_port = client_port
self.server_url = server_url
self.logger = LoggerFactory.getLogger("TrainMPCDistillationStrategy",
logging.INFO)
def __init__(self, job, data, fed_step, client_id, model, curve):
super(TrainStandloneNormalStrategy, self).__init__(job, data, fed_step, client_id, model, curve)
self.logger = LoggerFactory.getLogger("TrainStandloneNormalStrategy", logging.INFO)
def __init__(self):
self.job_path = JOB_PATH
self.logger = LoggerFactory.getLogger("JobManager", logging.INFO)
# limitations under the License.
import os
import json
import logging
from flask import Flask, send_from_directory, request
from werkzeug.serving import run_simple
from gfl.entity.runtime_config import CONNECTED_TRAINER_LIST
from gfl.core.job_manager import JobManager
from gfl.utils.utils import JobEncoder, return_data_decorator, LoggerFactory
API_VERSION = "/api/v1"
JOB_PATH = os.path.join(os.path.abspath("."), "res", "jobs_server")
BASE_MODEL_PATH = os.path.join(os.path.abspath("."), "res", "models")
logger = LoggerFactory.getLogger(__name__, logging.INFO)
app = Flask(__name__)
@app.route("/test/<name>")
@return_data_decorator
def test_flask_server(name):
return name, 200
@app.route("/register/<ip>/<port>/<client_id>",
methods=['POST'],
endpoint='register_trainer')
@return_data_decorator
def register_trainer(ip, port, client_id):
def __init__(self):
super(FLServer, self).__init__()
self.logger = LoggerFactory.getLogger("FlServer", logging.INFO)
def __init__(self, work_mode, job_path, base_model_path):
super(FedAvgAggregator, self).__init__(work_mode, job_path,
base_model_path)
self.fed_step = {}
self.logger = LoggerFactory.getLogger("FedAvgAggregator", logging.INFO)