code: def test_factorization_machines_serverless_inference(
      sagemaker_session, cpu_instance_type, training_set
  ):
      job_name = unique_name_from_base("fm-serverless")
  
      with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
          fm = FactorizationMachines(
              role="SageMakerRole",
              instance_count=1,
              instance_type=cpu_instance_type,
              num_factors=10,
              predictor_type="regressor",
              epochs=2,
              clip_gradient=1e2,
              eps=0.001,
              rescale_grad=1.0 / 100,
              sagemaker_session=sagemaker_session,
          )
  
          # training labels must be 'float32'
          fm.fit(
              fm.record_set(
                  training_set[0][:200],
                  training_set[1][:200].astype("float32"),
              ),
              job_name=job_name,
          )
  
      with timeout_and_delete_endpoint_by_name(
          job_name, sagemaker_session
      ):
          model = FactorizationMachinesModel(
              fm.model_data,
              role="SageMakerRole",
              sagemaker_session=sagemaker_session,
          )
          predictor = model.deploy(
              serverless_inference_config=ServerlessInferenceConfig(),
              endpoint_name=job_name,
          )
          result = predictor.predict(training_set[0][:10])
  
          assert len(result) == 10
          for record in result:
              assert record.label["score"] is not None
  
file_path: sagemaker-python-sdk/tests/integ/test_factorization_machines.py
imports: from __future__ import absolute_import
  import time
  import pytest
  from sagemaker import FactorizationMachines, FactorizationMachinesModel
  from sagemaker.serverless import ServerlessInferenceConfig
  from sagemaker.utils import unique_name_from_base
  from tests.integ import datasets, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
label_desc: Use image node_id 4 for calling a global function with example usage: test_factorization_machines_serverless_inference(sagemaker_session, cpu_instance_type, training_set) without return types