1.2 Option Configuration

The full options are shown as below

Category	Name	Type	Description	Default Value	Comment
Training Option	num_rounds	int	number of communication rounds	20
	proportion	float	proportion of clients sampled per round	0.2
	learning_rate_decay	float	learning rate decay for the training process	0.998	effective if lr_scheduler>-1
	lr_scheduler	int	type of the global learning rate scheduler	-1	effective if larger than -1
	early_stop	int	stop training if there is no improvement for no smaller than the maximum rounds	-1	effective if larger than -1
	num_epochs	int	number of epochs of local training	5
	num_steps	int	number of steps of local training, conflict with num_epochs	-1	dominates num_epochs if larger than 0
	learning_rate	float	learning rate of local training	0.1
	batch_size	int\float	batch size of local training	64	-1 means full batch, float value means the ratio of the full datasets
	optimizer	str	to select the optimizer of local training	'sgd'	'sgd','adam','rmsprop','adagrad'
	clip_grad	float	clipping gradients if the max norm of gradients \	\	g|| > clip_norm > 0
	momentum	float	momentum of local training	0.0
	weight_decay	float	weight decay of local training	0.0
	num_edge_rounds	int	number of edge rounds in hierFL	5	effective if scene is 'hierarchical'
	algo_para	int\list	algorithm-specific hyper-parameters	[]	the order should be consistent with the claim
	sample	str	to select sampling form	'uniform'	'uniform', 'md', 'full', x+'_with_availability'
	aggregate	str	to select aggregation form	'other'	'uniform', 'weighted_com', 'weighted_scale', 'other'
External Option	train_holdout	float	the rate of holding out the validation dataset from all the local training datasets	0.1
	test_holdout	float	the rate of holding out the validation dataset from the testing datasets owned by the server	0.0	effective if the server has no validation data
	local_test	bool	the local validation data will be equally split into validation and testing parts if True	False
	seed	int	seed for all the random modules	0
	dataseed	int	seed for all the random modules for local data train/val/test partition	0
	gpu	int\list	GPU IDs and empty input means using CPU	[]
	server_with_cpu	bool	the model parameters will be stored in the memory if True	False
	num_parallels	int	the number of parallels during communications	1
	num_workers	int	the number of workers of DataLoader	0
	pin_memory	bool	1)pin_memory of DataLoader, and 2) load data directly into memory	False
	test_batch_size	int	the batch_size used in testing phase	512
Simulator Option	availability	str	to select client availability mode	'IDL'	'IDL','YMF','MDF','LDF','YFF', 'HOMO','LN','SLN','YC'
	connectivity	str	to select client connectivity mode	'IDL'	'IDL','HOMO'
	completeness	str	to select client completeness mode	'IDL'	'IDL','PDU','FSU','ADU','ASU'
	responsiveness	str	to select client responsiveness mode	'IDL'	'IDL','LN','UNI'
Logger Option	log_level	str	the level of logger	'INFO'	'INFO','DEBUG'
	log_file	bool	whether log to file and default value is False	False
	no_log_console	bool	whether log to screen and default value is True	True
	no_overwrite	bool	whether to overwrite the old result	False
	eval_interval	int	evaluate every __ rounds;	1