mmdetection源码解读,本文就直接先train.py文件下手。 train.py文件 里面主要就两个函数,parse_args()和main()。 作用: parse_args():其实就是获取命令行参数的一个过程,从创建解析对象,到对其解析(有点拗口,但不是重点,只要知道,这个函数用来获得命令行的各个参数就行了。) main():函数主入口,先做了一些conf...
trainer_pipeline_file: Optional[str] = typer.Option( None, help="Trainer pipeline file path" None, "--trainer-pipeline-file", "-f", help="Trainer pipeline file path" ), daemon: Optional[bool] = daemon_option, list_train_type: Optional[bool] = list_train_type_option, show_config_limit...
import torchvision.transforms as transforms 3、创建一个config类,这个类在tools/train_classification_model.py中通过 from train_config import config引入。train_classification_model.py之所以能够正确引入这个config类实例,是因为 sys.path.append(args.work_dir)将train_config.py所在目录的路径添加到了sys路径中。
Search or jump to... Search code, repositories, users, issues, pull requests... Provide feedback We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your...
1、建库授权 MariaDB [(none)] CREATE DATABASE neutron; MariaDB [(none)]> GRANT ALL PRIVILEGES ON neutron.* TO 'neutron'@'localhost' IDENTIFIED BY 'NEUTRON_DBPASS'; MariaDB [(none)]> GRANT ALL PRIVILEGES ON neutron.* TO 'neutron'@'%' IDENTIFIED BY 'NEUTRON_DBPASS'; ...
<- Main config for evaluation │ └── train.yaml <- Main config for training ...
[root@openstack ~]#yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo 1. 2. 3.2 安装docker [root@openstack ~]#yum -y install docker-ce-18.03.1.ce-1.el7.centos 1. 3.3 配置docker,使用阿里加速器 ...
config=BertConfig.from_pretrained("bert-base-uncased")model=BertModel(config) 如果只需要 config 来构建模型,而不需要现成的预训练参数,可以参考下面的方法: config=BertConfig.from_json_file("your/path/to/config.json")model=Bert(config)bmt.init_parameters(model)# bmt.load(model,"your/path/to/pytor...
config: Path to the config file for NLU. # NLU的配置文件路径。 nlu_data: Path to the NLU training data. # NLU训练数据的路径。 output: Output path. # 输出路径。 fixed_model_name: Name of the model to be stored. # 要存储的模型的名称。
openstack-config --set /etc/octavia/octavia.conf haproxy_amphora key_path /etc/octavia/.ssh/octavia_ssh_key openstack-config --set /etc/octavia/octavia.conf haproxy_amphora base_path /var/lib/octavia openstack-config --set /etc/octavia/octavia.conf haproxy_amphora base_cert_dir /var/lib...