o mi(@sVddlZddlZddlZddlZddlmZmZddlmZ dee effddZ dS)N)AnyDict)filesreturncCsi}tjtjrVtjtjrVtd|d<ttj2}t | D]"\}}| d}t d|r8t|}n t d|rBt|}|||<q$Wdn1sQwYdtjvr}zi|ttjd}W|Stjy|tjdd d Y|Sw|S) aParses SageMaker configuration. Returns: A dictionary of SageMaker config keys/values or an empty dict if not found. SM_TRAINING_ENV is a json string of the training environment variables set by SageMaker and is only available when running in SageMaker, but not in local mode. SM_TRAINING_ENV is set by the SageMaker container and contains arguments such as hyperparameters and arguments passed to the training job. TRAINING_JOB_NAMEsagemaker_training_job_name"z ^-?[\d]+$z ^-?[.\d]+$NSM_TRAINING_ENVz5Failed to parse SM_TRAINING_ENV not valid JSON string) stacklevel)ospathexistssm_filesSM_PARAM_CONFIGSM_RESOURCE_CONFIGgetenvopenjsonloaditemsstriprematchintfloatenvironloadsJSONDecodeErrorwarningswarn)conffidkeyvalcastr'`/home/ubuntu/SoloSpeech/.venv/lib/python3.10/site-packages/wandb/integration/sagemaker/config.pyparse_sm_config s4       r)) rr rr typingrrrrstrr)r'r'r'r(s