config

Baseline for CKODE project

usage: python trainModel.py [-h] [--seed SEED] [--mech_path MECH_PATH] [--input_path INPUT_PATH]
                            [--label_path LABEL_PATH] [--shuffle] [--batch_size BATCH_SIZE]
                            [--valid_batch_size VALID_BATCH_SIZE] [--train_size TRAIN_SIZE]
                            [--valid_size VALID_SIZE] [--valid_ratio VALID_RATIO] [--prefetch PREFETCH]
                            [--num_workers NUM_WORKERS] [--pin_memory]
                            [--power_transform POWER_TRANSFORM] [--delta_t DELTA_T] [--dim DIM]
                            [-l LAYERS [LAYERS ...]] [--net_type NET_TYPE] [--actfun ACTFUN]
                            [--max_epoch MAX_EPOCH] [--epoch_decay EPOCH_DECAY] [-lr LEARNRATE]
                            [--lr_decay_rate LR_DECAY_RATE] [--batch_grow_rate BATCH_GROW_RATE]
                            [--lossfun LOSSFUN] [--optim OPTIM] [--modelname MODELNAME]
                            [--model_path MODEL_PATH] [--device DEVICE] [--n_gpu N_GPU] [-DP] [-DDP]
                            [--local_rank LOCAL_RANK] [-ws WORLD_SIZE] [--backend BACKEND]
                            [-note DESCRIPTION]

Named Arguments

--seed

random seed

Default: 2022

--mech_path

chemical mechnism file dir

--input_path

input dataset dir

--label_path

label dataset dir

--shuffle

shuffle the training dataset

Default: True

--batch_size

use for training duration per worker

Default: 1024

--valid_batch_size

use for validation duration per worker

Default: 8192

--train_size

training dataset size

--valid_size

validation dataset size

--valid_ratio

split percentages of training data as validation

Default: 0.1

--prefetch

use for training duration per worker

Default: 10

--num_workers

num_workers for dataloaders

Default: 16

--pin_memory

pin_memory for DataLoader

Default: True

--power_transform

power_transform for BCT

Default: 0.1

--delta_t

dnn time step

Default: 1e-06

--dim

feature dimention of data

Default: -1

-l, --layers

dnn hidden layers

Default: [1600, 800, 400]

--net_type

dnn type

Default: “fc”

--actfun

activation function

Default: “gelu”

--max_epoch

max epochs in training

Default: 5000

--epoch_decay

epoch interval for lr decay

Default: 2500

-lr, --learnrate

Default: 0.0001

--lr_decay_rate

learning rate decay

Default: 0.1

--batch_grow_rate

every [epoch_decay] batch_size grows

Default: 128

--lossfun

loss funtion: MSE,L1/MAE,CEl

Default: “L1”

--optim

optimizer for training

Default: “Adam”

--modelname

the dnn model name

--model_path

the dnn model dir

--device

device setup

Default: “cuda:0”

--n_gpu

gpu numbers of the machine

Default: 0

-DP, --use_DP

whether use torch.nn.DataParallel

Default: False

-DDP, --use_DDP

whether use DistributedDataParallel

Default: False

--local_rank

local rank

Default: -1

-ws, --world_size

world_size for DDP

Default: 1

--backend

current process backend for DDP, gloo,nccl,mpi

Default: “nccl”

-note, --description

description of the experiment(purpose/target/motivation)

Default: “test”