code: def _check_run_from_local_end_result(
      sagemaker_session, tc, is_complete_log=True
  ):
      assert tc.parameters == {
          "pa": 1.0,
          "pb": "p2-value",
          "pc": 2.0,
          "pd": "p4-value",
      }
  
      if not is_complete_log:
          return
  
      s3_prefix = f"s3://{sagemaker_session.default_bucket()}/{CUSTOM_S3_OBJECT_KEY_PREFIX}/{_DEFAULT_ARTIFACT_PREFIX}"
      assert s3_prefix in tc.output_artifacts[file_artifact_name].value
      assert (
          "text/plain"
          == tc.output_artifacts[file_artifact_name].media_type
      )
      assert "s3://Output" == tc.output_artifacts[artifact_name].value
      assert not tc.output_artifacts[artifact_name].media_type
      assert "s3://Input" == tc.input_artifacts[artifact_name].value
      assert not tc.input_artifacts[artifact_name].media_type
  
      assert len(tc.metrics) == 1
      metric_summary = tc.metrics[0]
      assert metric_summary.metric_name == metric_name
      assert metric_summary.max == 9.0
      assert metric_summary.min == 0.0
  
imports: from __future__ import absolute_import
  import datetime
  import json
  import os
  import time
  import pytest
  from tests.conftest import CUSTOM_S3_OBJECT_KEY_PREFIX
  from tests.integ.sagemaker.experiments.conftest import TAGS
  from sagemaker.experiments._api_types import _TrialComponentStatusType
  from sagemaker.experiments._utils import is_run_trial_component
  from sagemaker.processing import FrameworkProcessor
  from sagemaker.pytorch import PyTorch
  from sagemaker.s3 import S3Uploader
  from sagemaker.xgboost import XGBoostModel
  from tests.integ import DATA_DIR
  from sagemaker.experiments._metrics import BATCH_SIZE
  from sagemaker.experiments.trial_component import _TrialComponent
  from sagemaker.sklearn import SKLearn
  from sagemaker.utils import retry_with_backoff, unique_name_from_base
  from tests.integ.sagemaker.experiments.helpers import name, cleanup_exp_resources
  from sagemaker.experiments.run import RUN_NAME_BASE, DELIMITER
  from sagemaker.experiments import Run, load_run, list_runs
  from sagemaker.experiments._helper import _DEFAULT_ARTIFACT_PREFIX
label_desc: Use image node_id 16 for calling a global function with example usage: _check_run_from_local_end_result(sagemaker_session, tc, is_complete_log) without return types