code: def test_transformer(tfo, time, sagemaker_session):
      framework_model = DummyFrameworkModel(sagemaker_session)
      sparkml_model = SparkMLModel(
          model_data=MODEL_DATA_2,
          role=ROLE,
          sagemaker_session=sagemaker_session,
      )
      model_name = "ModelName"
      model = PipelineModel(
          models=[framework_model, sparkml_model],
          role=ROLE,
          sagemaker_session=sagemaker_session,
          name=model_name,
      )
  
      instance_count = 55
      strategy = "MultiRecord"
      assemble_with = "Line"
      output_path = "s3://output/path"
      output_kms_key = "output:kms:key"
      accept = "application/jsonlines"
      env = {"my_key": "my_value"}
      max_concurrent_transforms = 20
      max_payload = 5
      tags = [{"my_tag": "my_value"}]
      volume_kms_key = "volume:kms:key"
      transformer = model.transformer(
          instance_type=INSTANCE_TYPE,
          instance_count=instance_count,
          strategy=strategy,
          assemble_with=assemble_with,
          output_path=output_path,
          output_kms_key=output_kms_key,
          accept=accept,
          env=env,
          max_concurrent_transforms=max_concurrent_transforms,
          max_payload=max_payload,
          tags=tags,
          volume_kms_key=volume_kms_key,
      )
      assert transformer.instance_type == INSTANCE_TYPE
      assert transformer.instance_count == instance_count
      assert transformer.strategy == strategy
      assert transformer.assemble_with == assemble_with
      assert transformer.output_path == output_path
      assert transformer.output_kms_key == output_kms_key
      assert transformer.accept == accept
      assert transformer.env == env
      assert (
          transformer.max_concurrent_transforms
          == max_concurrent_transforms
      )
      assert transformer.max_payload == max_payload
      assert transformer.tags == tags
      assert transformer.volume_kms_key == volume_kms_key
      assert transformer.model_name == model_name
  
imports: from __future__ import absolute_import
  import copy
  import pytest
  from botocore.utils import merge_dicts
  from mock import Mock, patch
  from mock.mock import ANY
  from sagemaker.model import FrameworkModel
  from sagemaker.pipeline import PipelineModel
  from sagemaker.predictor import Predictor
  from sagemaker.session_settings import SessionSettings
  from sagemaker.sparkml import SparkMLModel
  from tests.unit import SAGEMAKER_CONFIG_MODEL, SAGEMAKER_CONFIG_ENDPOINT_CONFIG
label_desc: Use image node_id 6 for calling a global function with example usage: test_transformer(tfo, time, sagemaker_session) without return types