code: def test_call_fit(base_fit, sagemaker_session):
      fm = FactorizationMachines(
          base_job_name="fm",
          sagemaker_session=sagemaker_session,
          **ALL_REQ_ARGS,
      )
  
      data = RecordSet(
          "s3://{}/{}".format(BUCKET_NAME, PREFIX),
          num_records=1,
          feature_dim=FEATURE_DIM,
          channel="train",
      )
  
      fm.fit(data, MINI_BATCH_SIZE)
  
      base_fit.assert_called_once()
      assert len(base_fit.call_args[0]) == 2
      assert base_fit.call_args[0][0] == data
      assert base_fit.call_args[0][1] == MINI_BATCH_SIZE
  
imports: from __future__ import absolute_import
  import pytest
  from mock import Mock, patch
  from sagemaker import image_uris
  from sagemaker.amazon.factorization_machines import FactorizationMachines, FactorizationMachinesPredictor
  from sagemaker.amazon.amazon_estimator import RecordSet
  from sagemaker.session_settings import SessionSettings
label_desc: Use image node_id 10 for calling a global function with example usage: test_call_fit(base_fit, sagemaker_session) without return types