# Copyright (c) OpenMMLab. All rights reserved. import argparse import os.path as osp # Default using 4 gpu when training config_8gpu_list = [ 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py', # noqa 'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py', 'configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py', ] def parse_args(): parser = argparse.ArgumentParser( description='Convert benchmark model json to script') parser.add_argument( 'txt_path', type=str, help='txt path output by benchmark_filter') parser.add_argument('--port', type=int, default=24727, help='dist port') parser.add_argument( '--out', type=str, default='.dev/benchmark_train.sh', help='path to save model benchmark script') args = parser.parse_args() return args def create_train_bash_info(commands, config, script_name, partition, port): cfg = config.strip() # print cfg name echo_info = f'echo \'{cfg}\' &' commands.append(echo_info) commands.append('\n') _, model_name = osp.split(osp.dirname(cfg)) config_name, _ = osp.splitext(osp.basename(cfg)) # default setting if cfg in config_8gpu_list: command_info = f'GPUS=8 GPUS_PER_NODE=8 ' \ f'CPUS_PER_TASK=2 {script_name} ' else: command_info = f'GPUS=4 GPUS_PER_NODE=4 ' \ f'CPUS_PER_TASK=2 {script_name} ' command_info += f'{partition} ' command_info += f'{config_name} ' command_info += f'{cfg} ' command_info += f'--cfg-options ' \ f'checkpoint_config.max_keep_ckpts=1 ' \ f'dist_params.port={port} ' command_info += f'--work-dir work_dirs/{model_name}/{config_name} ' # Let the script shut up command_info += '>/dev/null &' commands.append(command_info) commands.append('\n') def main(): args = parse_args() if args.out: out_suffix = args.out.split('.')[-1] assert args.out.endswith('.sh'), \ f'Expected out file path suffix is .sh, but get .{out_suffix}' root_name = './tools' script_name = osp.join(root_name, 'slurm_train.sh') port = args.port partition_name = 'PARTITION=$1' commands = [] commands.append(partition_name) commands.append('\n') commands.append('\n') with open(args.txt_path, 'r') as f: model_cfgs = f.readlines() for i, cfg in enumerate(model_cfgs): create_train_bash_info(commands, cfg, script_name, '$PARTITION', port) port += 1 command_str = ''.join(commands) if args.out: with open(args.out, 'w') as f: f.write(command_str) if __name__ == '__main__': main()