Python Note [4] dict & set

dict   
d = {}
'A'  对应一个key 对应一个值 1
d[''] 查找

'' in d 检查是否有''
d.get(d['']) 检查是否有''
d.pop(d[''])删除
d['A'] = 2 直接替换
d['D'] = 4 增加
d内部存放关系与key没有关系;
dict占用空间大,搜索时间短
key 不可变,不可重复,list 不能作为 key; 字符串、整数可以


>>>d={'A':1, 'B':2, 'C':3}
>>>d['A']
1

>>>print ('D' in d) 

False
>>>print(d.get['D'],-1) 
-1
>>>print(d.get['D'])
None

set 是key的集合,无重复元素。可以输入重复元素,set会自动剔除。set内不可变,不能放入list

remove 删除
add 增加
s1 & s2 交集
s1 | s2 并集


>>>s = set([1,2,3,3])
>>>s1= ([1,2])
>>>s2 = ([2,3])
>>>print(s)
{1,2,3}
>>>s.add(4)
>>>print(s)
{1,2,3,4}

>>>print(s.add(4))
None

>>>s.remove(1)
>>>print(s)
{2,3,4}
>>>print(s1&s2)
>>>print(s1|s2)
 {2}
{1,2,3}


解释下面这段Python代码的内容。 #lane_with_angle_train.py import argparse import logging import os import os.path as osp from mmengine.config import Config, DictAction from mmengine.logging import print_log from mmengine.registry import RUNNERS from mmengine.runner import Runner from mmseg.utils import register_all_modules def parse_args(): parser = argparse.ArgumentParser(description='Train a segmentor') parser.add_argument('--config', help='train config file path') parser.add_argument('--work-dir', help='the dir to save logs and models') parser.add_argument( '--resume', action='store_true', default=False, help='resume from the latest checkpoint in the work_dir automatically') parser.add_argument( '--amp', action='store_true', default=False, help='enable automatic-mixed-precision training') parser.add_argument( '--cfg-options', nargs='+', action=DictAction, help='override some settings in the used config, the key-value pair ' 'in xxx=yyy format will be merged into config file. If the value to ' 'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' 'Note that the quotation marks are necessary and that no white space ' 'is allowed.') parser.add_argument( '--launcher', choices=['none', 'pytorch', 'slurm', 'mpi'], default='none', help='job launcher') parser.add_argument('--local_rank', type=int, default=0) args = parser.parse_args() if 'LOCAL_RANK' not in os.environ: os.environ['LOCAL_RANK'] = str(args.local_rank) return args def main(): args = parse_args() # HACK:Select the config file # args.config = r'configs/angle_lane_experiment/fcn_res/alldata_configs/fcn_res18/fcn_res18_with_angleloss_with_anglefusion_5h.py' args.config = r'/root/angle-lane-mmseg/local_configs/da_res/da_res_mmlab_alldata.py' # register all modules in mmseg into the registries # do not init the default scope here because it will be init in the runner register_all_modules(init_default_scope=False) # load config cfg = Config.fromfile(args.config) cfg.launcher = args.launcher if args.cfg_options is not None: cfg.merge_from_dict(args.cfg_options) # work_dir is determined in this priority: CLI > segment in file > filename if args.work_dir is not None: # update configs according to CLI args if args.work_dir is not None cfg.work_dir = args.work_dir elif cfg.get('work_dir', None) is None: # use config filename as default work_dir if cfg.work_dir is None cfg.work_dir = osp.join('./work_dirs', osp.splitext(osp.basename(args.config))[0]) # enable automatic-mixed-precision training if args.amp is True: optim_wrapper = cfg.optim_wrapper.type if optim_wrapper == 'AmpOptimWrapper': print_log( 'AMP training is already enabled in your config.', logger='current', level=logging.WARNING) else: assert optim_wrapper == 'OptimWrapper', ( '`--amp` is only supported when the optimizer wrapper type is ' f'`OptimWrapper` but got {optim_wrapper}.') cfg.optim_wrapper.type = 'AmpOptimWrapper' cfg.optim_wrapper.loss_scale = 'dynamic' # resume training cfg.resume = args.resume # build the runner from config if 'runner_type' not in cfg: # build the default runner runner = Runner.from_cfg(cfg) else: # build customized runner from the registry # if 'runner_type' is set in the cfg runner = RUNNERS.build(cfg) # start training runner.train() if __name__ == '__main__': main()
08-28
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