code: def test_incremental_training_with_unsupported_model_logs_warning(
      self,
      mock_estimator_deploy: mock.Mock,
      mock_estimator_fit: mock.Mock,
      mock_estimator_init: mock.Mock,
      mock_get_model_specs: mock.Mock,
      mock_session_estimator: mock.Mock,
      mock_session_model: mock.Mock,
      mock_logger_warning: mock.Mock,
      mock_supports_incremental_training: mock.Mock,
      mock_is_valid_model_id: mock.Mock,
  ):
      mock_is_valid_model_id.return_value = True
  
      mock_estimator_deploy.return_value = default_predictor
  
      model_id = "js-trainable-model"
  
      mock_get_model_specs.side_effect = get_special_model_spec
  
      mock_session_estimator.return_value = sagemaker_session
      mock_session_model.return_value = sagemaker_session
  
      mock_supports_incremental_training.return_value = False
  
      JumpStartEstimator(
          model_id=model_id,
          model_uri="some-weird-model-uri",
      )
  
      mock_logger_warning.assert_called_once_with(
          "'%s' does not support incremental training but is being trained with non-default model artifact.",
          model_id,
      )
      mock_supports_incremental_training.assert_called_once_with(
          model_id=model_id,
          model_version="*",
          region=region,
          tolerate_deprecated_model=False,
          tolerate_vulnerable_model=False,
          sagemaker_session=sagemaker_session,
      )
  
imports: from __future__ import absolute_import
  import time
  from typing import Optional, Set
  from unittest import mock
  import unittest
  from inspect import signature
  import pytest
  from sagemaker.async_inference.async_inference_config import AsyncInferenceConfig
  from sagemaker.debugger.profiler_config import ProfilerConfig
  from sagemaker.estimator import Estimator
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.jumpstart.artifacts.environment_variables import _retrieve_default_environment_variables
  from sagemaker.jumpstart.artifacts.hyperparameters import _retrieve_default_hyperparameters
  from sagemaker.jumpstart.artifacts.metric_definitions import _retrieve_default_training_metric_definitions
  from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION
  from sagemaker.jumpstart.enums import JumpStartScriptScope, JumpStartTag
  from sagemaker.jumpstart.estimator import JumpStartEstimator
  from sagemaker.jumpstart.utils import get_jumpstart_content_bucket
  from sagemaker.session_settings import SessionSettings
  from tests.integ.sagemaker.jumpstart.utils import get_training_dataset_for_model_and_version
  from sagemaker.model import Model
  from sagemaker.predictor import Predictor
  from tests.unit.sagemaker.jumpstart.utils import get_special_model_spec, overwrite_dictionary
label_desc: Use image node_id 17 for calling the EstimatorTest obj's underlying member method code with example usage: obj.test_incremental_training_with_unsupported_model_logs_warning(mock_estimator_deploy, mock_estimator_fit, mock_estimator_init, mock_get_model_specs, mock_session_estimator, mock_session_model, mock_logger_warning, mock_supports_incremental_training, mock_is_valid_model_id) without return types