class_docstr: A SageMakerClient that implements the API calls locally.
  
  Used for doing local training and hosting local endpoints. It still needs access to
  a boto client to interact with S3 but it won't perform any SageMaker call.
  
  Implements the methods with the same signature as the boto SageMakerClient.
  
  Args:
  
  Returns:
class_docstr_tok: ["A","SageMakerClient","that","implements","the","API","calls","locally",".","Used","for","doing","local","training","and","hosting","local","endpoints",".","It","still","needs","access","to","a","boto","client","to","interact","with","S3","but","it","wo","n't","perform","any","SageMaker","call",".","Implements","the","methods","with","the","same","signature","as","the","boto","SageMakerClient",".","Args",":","Returns",":"]
docstr: Start the pipeline.
  
  Args:
    PipelineName (str):
  
  Returns: _LocalPipelineExecution object
code: def start_pipeline_execution(self, PipelineName, **kwargs):
      """Start the pipeline.
  
      Args:
        PipelineName (str):
  
      Returns: _LocalPipelineExecution object
  
      """
      if "ParallelismConfiguration" in kwargs:
          logger.warning(
              "Parallelism configuration is not supported in local mode."
          )
      if "SelectiveExecutionConfig" in kwargs:
          raise ValueError(
              "SelectiveExecutionConfig is not supported in local mode."
          )
      if PipelineName not in LocalSagemakerClient._pipelines:
          error_response = {
              "Error": {
                  "Code": "ResourceNotFound",
                  "Message": "Pipeline {} does not exist".format(
                      PipelineName
                  ),
              }
          }
          raise ClientError(error_response, "start_pipeline_execution")
      return LocalSagemakerClient._pipelines[PipelineName].start(
          **kwargs
      )
  
imports: from __future__ import absolute_import, annotations
  import logging
  import platform
  from datetime import datetime
  from typing import Dict
  import boto3
  from botocore.exceptions import ClientError
  import jsonschema
  from sagemaker.config import SAGEMAKER_PYTHON_SDK_LOCAL_MODE_CONFIG_SCHEMA, SESSION_DEFAULT_S3_BUCKET_PATH, SESSION_DEFAULT_S3_OBJECT_KEY_PREFIX_PATH, load_local_mode_config, load_sagemaker_config, validate_sagemaker_config
  from sagemaker.local.image import _SageMakerContainer
  from sagemaker.local.utils import get_docker_host
  from sagemaker.local.entities import _LocalEndpointConfig, _LocalEndpoint, _LocalModel, _LocalProcessingJob, _LocalTrainingJob, _LocalTransformJob, _LocalPipeline
  from sagemaker.session import Session
  from sagemaker.utils import get_config_value, _module_import_error, resolve_value_from_config, format_tags
label_desc: Use image node_id 22 for calling the LocalSagemakerClient obj's underlying member method code with example usage: obj.start_pipeline_execution(PipelineName) and returns: LocalSagemakerClient