AI开发平台MODELARTS-使用ModelArts SDK:示例代码

时间：2024-06-17 17:55:57

AI开发平台MODELARTS JupyterLab

示例代码

创建训练作业

    
     
       
       
         from modelarts.session import Session
from modelarts.estimator import Estimator
session = Session()
estimator = Estimator(
                      modelarts_session=session,
                      framework_type='PyTorch',                                     # AI引擎名称
                      framework_version='PyTorch-1.0.0-python3.6',                  # AI引擎版本
                      code_dir='/obs-bucket-name/src/',                             # 训练脚本目录
                      boot_file='/obs-bucket-name/src/pytorch_sentiment.py',        # 训练启动脚本目录 
                      log_url='/obs-bucket-name/log/',                              # 训练日志目录
                      hyperparameters=[
                                       {"label":"classes",
                                        "value": "10"},    
                                       {"label":"lr",
                                        "value": "0.001"}
                                       ],
                      output_path='/obs-bucket-name/output/',                         # 训练输出目录
                      train_instance_type='modelarts.vm.xxx.xxx',                  # 训练环境规格
                      train_instance_count=1,                                       # 训练节点个数
                      job_description='pytorch-sentiment with ModelArts SDK')       # 训练作业描述
job_instance = estimator.fit(inputs='/obs-bucket-name/data/train/', wait=False, job_name='my_training_job')

        

      

    
   

查询模型列表

    
         from modelarts.session import Session 
from modelarts.model import Model
session = Session() 
model_list_resp = Model.get_model_list(session, model_status="published", model_name="digit", order="desc")

查询服务详情

    
         from modelarts.session import Session
from modelarts.model import Predictor
session = Session()
predictor_instance = Predictor(session, service_id="input your service_id")
predictor_info_resp = predictor_instance.get_service_info()