os.popen("bash command).read() 运行shell命令,获取执行结果 和环境变量相关的 1 os.environ 获取系统环境变量 和操作系统路径相关的os.path 1 2 3 4 5 6 7 8 9 10 11 12 13 os.path.abspath(path) 返回path规范化的绝对路径 os.path.split(path) 将path分割成目录和文件名二元组返回 os.path.dirna...
importosos.environ["HYRIVER_CACHE_NAME"]="path/to/aiohttp_cache.sqlite"os.environ["HYRIVER_CACHE_NAME_HTTP"]="path/to/http_cache.sqlite"os.environ["HYRIVER_CACHE_EXPIRE"]="3600"os.environ["HYRIVER_CACHE_DISABLE"]="true"os.environ["HYRIVER_SSL_CERT"]="path/to/cert.pem" ...
参考链接： C++ acos() #include <math.h> #define PI acos(-1) 主要是利用利用数学函数中的反...
import gc import os os.environ["CUDA_VISIBLE_DEVICES"] = "-1" import tensorflow as tf import tracemalloc import linecache def display_top(snapshot, key_type='lineno', limit=3): snapshot = snapshot.filter_traces(( tracemalloc.Filter(False, "<frozen importlib._bootstrap>"), tracemalloc.Filt...
importosimportloggingimportboto3importpsycopg2 HOST=os.environ['hostname']USER=os.environ['username']NEWPASSVAL=os.environ['passwordvalue']DBNAME=os.getenv('DBNAME',os.environ['dbname'])SNS_TOPIC_ARN=os.getenv('topicarn')logger=logging.getLogger()logger.setLevel(logging.INFO)SNS=boto3.client('...
#每N个批次打印一次结果 'save_steps': 500, #每N个批次保存一次模型参数 "checkpoints": "/home/aistudio/work/checkpoints" #保存的路径 } def seed_paddle(seed=1024): seed = int(seed) random.seed(seed) os.environ['PYTHONHASHSEED'] = str(seed) np.random.seed(seed) paddle.seed(seed) see...
//train.py###deepspeed.init_distributed()args.local_rank=int(os.environ['LOCAL_RANK'])###defprepare_data():...model=BaiChuanForCausalLM(smallconfig)torch.cuda.set_device(args.local_rank)...deftrain(data_engine,model_engine):model_engine.train()local_rank=int(os.environ['LOCAL_RANK'])...
Thermochemical conversion technologies present an opportunity to flip the paradigm of wastewater biosolids management operations from energy-intense and expensive waste management processes into energy-positive and economical resource extraction centers.
While illegal, unreported, and unregulated (IUU) fishing is a premier issue facing ocean sustainability, characterizing it is challenging due to its clandestine nature. Current approaches can be resource intensive and sometimes controversial. Using Chile as an example, we present a structured process ...
importos # Intel Extension for TensorFlow Optimizations os.environ['TF_ENABLE_ONEDNN_OPT']="1"os.environ[TF_ENABLE_MKL_NATIVE_FORMAT']="1" # KMP Optimizations os.environ['KMP_BLOCKTIME']="0"os.environ['KMP_AFFINITY']="granularity=fine,compact,1,0"os.environ['KMP_SETTINGS'...