code: def test_object2vec(sagemaker_session, cpu_instance_type):
      job_name = unique_name_from_base("object2vec")
  
      with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
          data_path = os.path.join(DATA_DIR, "object2vec")
          data_filename = "train.jsonl"
  
          with open(os.path.join(data_path, data_filename), "r") as f:
              num_records = len(f.readlines())
  
          object2vec = Object2Vec(
              role="SageMakerRole",
              instance_count=1,
              instance_type=cpu_instance_type,
              epochs=3,
              enc0_max_seq_len=20,
              enc0_vocab_size=45000,
              enc_dim=16,
              num_classes=3,
              negative_sampling_rate=0,
              comparator_list="hadamard,concat,abs_diff",
              tied_token_embedding_weight=False,
              token_embedding_storage_type="dense",
              sagemaker_session=sagemaker_session,
          )
  
          record_set = prepare_record_set_from_local_files(
              data_path,
              object2vec.data_location,
              num_records,
              FEATURE_NUM,
              sagemaker_session,
          )
  
          object2vec.fit(records=record_set, job_name=job_name)
  
      with timeout_and_delete_endpoint_by_name(
          job_name, sagemaker_session
      ):
          model = Object2VecModel(
              object2vec.model_data,
              role="SageMakerRole",
              sagemaker_session=sagemaker_session,
          )
          predictor = model.deploy(
              1, cpu_instance_type, endpoint_name=job_name
          )
          assert isinstance(predictor, Predictor)
  
          predict_input = {
              "instances": [{"in0": [354, 623], "in1": [16]}]
          }
  
          result = predictor.predict(predict_input)
  
          assert len(result) == 1
          for record in result:
              assert record.label["scores"] is not None
  
file_path: sagemaker-python-sdk/tests/integ/test_object2vec.py
imports: from __future__ import absolute_import
  import os
  import pytest
  from sagemaker.predictor import Predictor
  from sagemaker import Object2Vec, Object2VecModel
  from sagemaker.serverless import ServerlessInferenceConfig
  from sagemaker.utils import unique_name_from_base
  from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
  from tests.integ.record_set import prepare_record_set_from_local_files
label_desc: Use image node_id 1 for calling a global function with example usage: test_object2vec(sagemaker_session, cpu_instance_type) without return types