Python利用omegaconf库轻松实现配置文件管理

pip install omegaconf

from omegaconf import OmegaConf

# 通过字典创建
config = OmegaConf.create({
    'model': {
        'name': 'resnet50',
        'lr': 0.001
    },
    'batch_size': 32
})

print(config.model.name)  # 输出：resnet50
print(config.batch_size)   # 输出：32

# 通过YAML字符串创建
yaml_config = OmegaConf.create('''
model:
  name: resnet101
  lr: 0.0005
batch_size: 64
''')

print(yaml_config.model.lr)  # 输出：0.0005

# 修改配置
config.model.lr = 0.01
print(config.model.lr)  # 输出：0.01

# 动态添加新参数
config.new_param = 'hello'
print(config.new_param)  # 输出：hello

config1 = OmegaConf.create({
    'model': {
        'name': 'resnet50',
        'lr': 0.001
    }
})

config2 = OmegaConf.create({
    'model': {
        'lr': 0.0001  # 更新学习率
    },
    'batch_size': 64
})

merged_config = OmegaConf.merge(config1, config2)
print(merged_config)

yaml_config = OmegaConf.create('''
path: /data
filename: data.csv
full_path: ${path}/${filename}
''')

print(yaml_config.full_path)  # 输出：/data/data.csv

from omegaconf import OmegaConf
import argparse

# 默认配置
default_config = OmegaConf.create({
    'learning_rate': 0.001,
    'batch_size': 32
})

# 解析命令行参数
parser = argparse.ArgumentParser()
parser.add_argument('--learning_rate', type=float)
args = parser.parse_args()

# 合并配置
cli_config = OmegaConf.from_dotlist([f'learning_rate={args.learning_rate}'])
final_config = OmegaConf.merge(default_config, cli_config)
print(final_config)

base_config = OmegaConf.create({
    'dataset': {
        'path': '/data',
        'type': 'csv'
    }
})

dev_config = OmegaConf.create({
    'dataset': {
        'path': '/dev_data'
    }
})

deploy_config = OmegaConf.merge(base_config, dev_config)
print(deploy_config.dataset.path)  # 输出：/dev_data