class_docstr: Lineage Artifact Tracker
class_docstr_tok: ["Lineage","Artifact","Tracker"]
docstr: Initialize a `_LineageArtifactTracker` instance.
  
  Args:
      trial_component_arn (str): The ARN of the trial component to be
          associated with the input/output artifacts.
      sagemaker_session (sagemaker.session.Session): Session object which
          manages interactions with Amazon SageMaker APIs and any other
          AWS services needed.
docstr_tok: ["Initialize","a","`","_LineageArtifactTracker","`","instance",".","Args",":","trial_component_arn","(","str",")",":","The","ARN","of","the","trial","component","to","be","associated","with","the","input\/output","artifacts",".","sagemaker_session","(","sagemaker.session.Session",")",":","Session","object","which","manages","interactions","with","Amazon","SageMaker","APIs","and","any","other","AWS","services","needed","."]
code: def __init__(self, trial_component_arn, sagemaker_session):
      """Initialize a `_LineageArtifactTracker` instance.
  
      Args:
          trial_component_arn (str): The ARN of the trial component to be
              associated with the input/output artifacts.
          sagemaker_session (sagemaker.session.Session): Session object which
              manages interactions with Amazon SageMaker APIs and any other
              AWS services needed.
      """
      self.trial_component_arn = trial_component_arn
      self.sagemaker_session = sagemaker_session
      self.artifacts = []
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  import botocore
  from sagemaker import s3
  from sagemaker.experiments._utils import is_already_exist_error
label_desc: Use image node_id 1 to create a new _LineageArtifactTracker object from inherited base classes: object with example: obj = _LineageArtifactTracker(trial_component_arn, sagemaker_session)