code: def _make_pipeline(self, pipeline_root, pipeline_run_id):
      pipeline = test_pipeline_with_resolver.create_pipeline()
      runtime_parameter_utils.substitute_runtime_parameter(
          pipeline,
          {
              constants.PIPELINE_ROOT_PARAMETER_NAME: pipeline_root,
              constants.PIPELINE_RUN_ID_PARAMETER_NAME: pipeline_run_id,
          },
      )
      return pipeline
  
imports: import os
  import uuid
  import tensorflow
  from tfx import types
  from tfx.dsl.compiler import constants
  from tfx.orchestration.experimental.core import post_execution_utils
  from tfx.orchestration.experimental.core import sync_pipeline_task_gen
  from tfx.orchestration.experimental.core import task_queue
  from tfx.orchestration.experimental.core import task_scheduler
  from tfx.orchestration.experimental.core import test_utils
  from tfx.orchestration.experimental.core.task_schedulers import resolver_task_scheduler
  from tfx.orchestration.experimental.core.testing import test_pipeline_with_resolver
  from tfx.orchestration import mlmd_connection_manager
  from tfx.orchestration.portable import execution_publish_utils
  from tfx.orchestration.portable import runtime_parameter_utils
  from tfx.orchestration.portable.mlmd import context_lib
  from tfx.utils import status
label_desc: Use image node_id 2 for calling the ResolverTaskSchedulerTest obj's underlying member method code with example usage: obj._make_pipeline(pipeline_root, pipeline_run_id) and returns: pipeline