code: def test_gated_model_training_v2_neuron(setup):
      model_id = "meta-textgenerationneuron-llama-2-7b"
  
      estimator = JumpStartEstimator(
          model_id=model_id,
          role=get_sm_session().get_caller_identity_arn(),
          sagemaker_session=get_sm_session(),
          tags=[
              {
                  "Key": JUMPSTART_TAG,
                  "Value": os.environ[
                      ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID
                  ],
              }
          ],
          environment={"accept_eula": "true"},
          max_run=259200,  # avoid exceeding resource limits
      )
  
      # uses ml.trn1.32xlarge instance
      estimator.fit(
          {
              "training": f"s3://{get_jumpstart_content_bucket(JUMPSTART_DEFAULT_REGION_NAME)}/"
              f"{get_training_dataset_for_model_and_version(model_id, '*')}",
          }
      )
  
      # uses ml.inf2.xlarge instance
      predictor = estimator.deploy(
          tags=[
              {
                  "Key": JUMPSTART_TAG,
                  "Value": os.environ[
                      ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID
                  ],
              }
          ],
          role=get_sm_session().get_caller_identity_arn(),
          sagemaker_session=get_sm_session(),
      )
  
      payload = {
          "inputs": "some-payload",
      }
  
      response = predictor.predict(
          payload, custom_attributes="accept_eula=true"
      )
  
      assert response is not None
  
file_path: sagemaker-python-sdk/tests/integ/sagemaker/jumpstart/estimator/test_jumpstart_estimator.py
imports: from __future__ import absolute_import
  import os
  import time
  import mock
  import pytest
  from sagemaker.jumpstart.constants import JUMPSTART_DEFAULT_REGION_NAME
  from sagemaker.jumpstart.estimator import JumpStartEstimator
  import tests
  from tests.integ.sagemaker.jumpstart.constants import ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID, JUMPSTART_TAG
  from tests.integ.sagemaker.jumpstart.utils import get_sm_session, get_training_dataset_for_model_and_version, x_fail_if_ice
  from sagemaker.jumpstart.utils import get_jumpstart_content_bucket
label_desc: Use image node_id 4 for calling a global function with example usage: test_gated_model_training_v2_neuron(setup) without return types