Fix args changes in examples and utils

docs/Femnist_stats.md

@@ -15,10 +15,10 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 # Make sure you have downloaded and installed FedScale
+import fedscale.core.config_parser as parser
 from fedscale.dataloaders.femnist import FEMNIST
 from fedscale.dataloaders.utils_data import get_data_transform
 from fedscale.dataloaders.divide_data import DataPartitioner
-from fedscale.core.config_parser import args
 ```
 
 
@@ -33,10 +33,10 @@ test_dataset = FEMNIST('./benchmark/dataset/data/femnist', dataset='test', trans
 Partition the dataset by the `client_data_mapping` file, which gives the real-world client-level heterogeneity.
 
 ```{code-cell}
-args.task = 'cv'
-training_sets = DataPartitioner(data=train_dataset, args=args, numOfClass=62)
+parser.args.task = 'cv'
+training_sets = DataPartitioner(data=train_dataset, args=parser.args, numOfClass=62)
 training_sets.partition_data_helper(num_clients=None, data_map_file='./benchmark/dataset/data/femnist/client_data_mapping/train.csv')
-#testing_sets = DataPartitioner(data=test_dataset, args=args, numOfClass=62, isTest=True)
+#testing_sets = DataPartitioner(data=test_dataset, args=parser.args, numOfClass=62, isTest=True)
 #testing_sets.partition_data_helper(num_clients=None, data_map_file='./benchmark/dataset/data/femnist/client_data_mapping/train.csv')
 ```
 
@@ -76,7 +76,7 @@ rank=1
 isTest = False
 dropLast =  True
 partition = training_sets.use(rank - 1, isTest)
-num_loaders = min(int(len(partition)/ args.batch_size/2),  args.num_loaders)
+num_loaders = min(int(len(partition)/ parser.args.batch_size/2),  parser.args.num_loaders)
 dataloader = DataLoader(partition, batch_size=16, shuffle=True, pin_memory=True, timeout=60, num_workers=num_loaders, drop_last=dropLast)
 ```
 

examples/heterofl/customized_fllibs.py

@@ -9,14 +9,14 @@
 import torch.nn.functional as F
 from resnet_heterofl import resnet18
 
-from fedscale.core.config_parser import args
+import fedscale.core.config_parser as parser
 
 
 def init_model():
     global tokenizer
 
     logging.info("Initializing the model ...")
-    if args.model == 'resnet_heterofl':
+    if parser.args.model == 'resnet_heterofl':
         model = resnet18()
 
     return model