AI开发平台ModelArts-使用ModelArts SDK:示例代码

时间：2023-11-01 16:16:40

AI开发平台ModelArts 使用JupyterLab

示例代码

创建训练作业

    
         from modelarts.session import Sessionfrom modelarts.estimator import Estimatorsession = 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.gpu.p100',                  # 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 Modelsession = 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 Sessionfrom modelarts.model import Predictorsession = Session()predictor_instance = Predictor(session, service_id="input your service_id")predictor_info_resp = predictor_instance.get_service_info()