Merge pull request #4 from aidecentralized/configs

config changes

src/configs/algo_config.py

@@ -0,0 +1,19 @@
+# Algorithm Configuration
+
+iid_dispfl_clients_new = {
+    "algo": "dispfl",
+    "exp_id": 200,
+    "exp_type": "iid_dispfl",
+    "neighbors": 2,
+    "active_rate": 0.8,
+    "dense_ratio": 0.5,
+    "erk_power_scale": 1,
+    "anneal_factor": 0.5,
+    "epochs": 1000,
+    "model": "resnet34",
+    "model_lr": 3e-4,
+    "batch_size": 128,
+    "exp_keys": []
+}
+
+current_config = iid_dispfl_clients_new

src/configs/sys_config.py

@@ -0,0 +1,11 @@
+# System Configuration
+system_config = {
+    "num_users": 4,
+    "experiment_path": "./experiments/",
+    "dset": "cifar10",
+    "dump_dir": "./expt_dump/",
+    "dpath": "/data/unagi0/anakewat/imgs/",
+    "seed": 2,
+    "device_ids": {"node_0": [5], "node_1": [5],"node_2": [5], "node_3": [2], "node_4": [2], "node_5": [3], "node_6": [3], "node_7": [3], "node_8": [3]},
+    "dataset_splits": {"samples_per_user": 500}, #iid, same structure for non_iid
+}

src/scheduler.py

@@ -1,5 +1,7 @@
 from mpi4py import MPI
-import torch, random, numpy
+import torch
+import random
+import numpy
 from algos.base_class import BaseNode
 from algos.fl import FedAvgClient, FedAvgServer
 from algos.isolated import IsolatedServer
@@ -12,15 +14,15 @@
 from algos.fl_ring import FedRingClient, FedRingServer
 from algos.swarm import SWARMClient, SWARMServer
 from algos.DisPFL import DisPFLClient, DisPFLServer
-from algos.def_kt import DefKTClient,DefKTServer
+from algos.def_kt import DefKTClient, DefKTServer
 from algos.fedfomo import FedFomoClient, FedFomoServer
 from algos.L2C import L2CClient, L2CServer
 from algos.MetaL2C import MetaL2CClient, MetaL2CServer
 from algos.fl_central import CentralizedCLient, CentralizedServer
 from algos.fl_data_repr import FedDataRepClient, FedDataRepServer
 from algos.fl_val import FedValClient, FedValServer
 from utils.log_utils import copy_source_code, check_and_create_path
-from utils.config_utils import load_config, process_config
+from utils.config_utils import load_config, process_config, get_device_ids
 import os
 
 # should be used as: algo_map[algo_name][rank>0](config)
@@ -37,32 +39,48 @@
     "fedring": [FedRingServer,FedRingClient],
     "swarm" : [SWARMServer, SWARMClient],
     "dispfl": [DisPFLServer, DisPFLClient],
-    "defkt": [DefKTServer,DefKTClient],
+    "defkt": [DefKTServer, DefKTClient],
     "fedfomo": [FedFomoServer, FedFomoClient],
-    "l2c": [L2CServer,L2CClient],
-    "metal2c": [MetaL2CServer,MetaL2CClient],
+    "l2c": [L2CServer, L2CClient],
+    "metal2c": [MetaL2CServer, MetaL2CClient],
     "centralized": [CentralizedServer, CentralizedCLient],
     "feddatarepr": [FedDataRepServer, FedDataRepClient],
     "fedval": [FedValServer, FedValClient],
 }
 
+
 def get_node(config: dict, rank) -> BaseNode:
     algo_name = config["algo"]
-    return algo_map[algo_name][rank>0](config)
+    return algo_map[algo_name][rank > 0](config)
 
 
 class Scheduler():
     """ Manages the overall orchestration of experiments
     """
+
     def __init__(self) -> None:
         pass
 
-    def assign_config_by_path(self, config_path) -> None:
-        self.config = load_config(config_path)
-
     def install_config(self) -> None:
         self.config = process_config(self.config)
 
+    def assign_config_by_path(self, sys_config_path, algo_config_path):
+        self.sys_config = load_config(sys_config_path)
+        self.algo_config = load_config(algo_config_path)
+        self.merge_configs()
+
+    def merge_configs(self):
+        self.config = self.algo_config.copy()
+        self.config.update({
+            "dset": self.sys_config["dset"],
+            "dump_dir": self.sys_config["dump_dir"],
+            "dpath": self.sys_config["dpath"],
+            "num_users": self.sys_config["num_users"],
+            "seed": self.config["seed"],
+            "samples_per_user": self.sys_config["dataset_splits"]["samples_per_user"],
+            "device_ids": self.sys_config["device_ids"]
+        })
+
     def initialize(self, copy_souce_code=True) -> None:
         assert self.config is not None, "Config should be set when initializing"
 
@@ -71,7 +89,9 @@ def initialize(self, copy_souce_code=True) -> None:
 
         # Base clients modify the seed later on
         seed = self.config["seed"]
-        torch.manual_seed(seed); random.seed(seed); numpy.random.seed(seed)
+        torch.manual_seed(seed)
+        random.seed(seed)
+        numpy.random.seed(seed)
 
         if rank == 0:
             if copy_souce_code: