class_docstr: Experiment config for SageMaker pipeline.
class_docstr_tok: ["Experiment","config","for","SageMaker","pipeline","."]
docstr: Create a PipelineExperimentConfig
  
  Examples:
  Use pipeline name as the experiment name and pipeline execution id as the trial name::
  
      PipelineExperimentConfig(
          ExecutionVariables.PIPELINE_NAME, ExecutionVariables.PIPELINE_EXECUTION_ID)
  
  Use a customized experiment name and pipeline execution id as the trial name::
  
      PipelineExperimentConfig(
          'MyExperiment', ExecutionVariables.PIPELINE_EXECUTION_ID)
  
  Args:
      experiment_name (Union[str, Parameter, ExecutionVariable, Expression]):
          the name of the experiment that will be created.
      trial_name (Union[str, Parameter, ExecutionVariable, Expression]):
          the name of the trial that will be created.
docstr_tok: ["Create","a","PipelineExperimentConfig","Examples",":","Use","pipeline","name","as","the","experiment","name","and","pipeline","execution","id","as","the","trial","name",":",":","PipelineExperimentConfig","(","ExecutionVariables.PIPELINE_NAME",",","ExecutionVariables.PIPELINE_EXECUTION_ID",")","Use","a","customized","experiment","name","and","pipeline","execution","id","as","the","trial","name",":",":","PipelineExperimentConfig","(","'MyExperiment","'",",","ExecutionVariables.PIPELINE_EXECUTION_ID",")","Args",":","experiment_name","(","Union","[","str",",","Parameter",",","ExecutionVariable",",","Expression","]",")",":","the","name","of","the","experiment","that","will","be","created",".","trial_name","(","Union","[","str",",","Parameter",",","ExecutionVariable",",","Expression","]",")",":","the","name","of","the","trial","that","will","be","created","."]
code: def __init__(
      self,
      experiment_name: Union[
          str, Parameter, ExecutionVariable, Expression
      ],
      trial_name: Union[str, Parameter, ExecutionVariable, Expression],
  ):
      """Create a PipelineExperimentConfig
  
      Examples:
      Use pipeline name as the experiment name and pipeline execution id as the trial name::
  
          PipelineExperimentConfig(
              ExecutionVariables.PIPELINE_NAME, ExecutionVariables.PIPELINE_EXECUTION_ID)
  
      Use a customized experiment name and pipeline execution id as the trial name::
  
          PipelineExperimentConfig(
              'MyExperiment', ExecutionVariables.PIPELINE_EXECUTION_ID)
  
      Args:
          experiment_name (Union[str, Parameter, ExecutionVariable, Expression]):
              the name of the experiment that will be created.
          trial_name (Union[str, Parameter, ExecutionVariable, Expression]):
              the name of the trial that will be created.
      """
      self.experiment_name = experiment_name
      self.trial_name = trial_name
  
file_path: sagemaker-python-sdk/src/sagemaker/workflow/pipeline_experiment_config.py
imports: from __future__ import absolute_import
  from typing import Union
  from sagemaker.workflow.parameters import Parameter
  from sagemaker.workflow.execution_variables import ExecutionVariable
  from sagemaker.workflow.entities import Entity, Expression, RequestType
label_desc: Use image node_id 1 to create a new PipelineExperimentConfig object from inherited base classes: Entity with example: obj = PipelineExperimentConfig(experiment_name, trial_name)