code: def test_load_from_feature_group_with_iceberg_table_format(
      describe_fg_response,
      spark_session_factory,
      spark_session,
      environment_helper,
  ):
      describe_iceberg_fg_response = describe_fg_response.copy()
      describe_iceberg_fg_response["OfflineStoreConfig"][
          "TableFormat"
      ] = "Iceberg"
      mocked_session = Mock(
          Session,
          describe_feature_group=Mock(
              return_value=describe_iceberg_fg_response
          ),
      )
      mock_input_loader = SparkDataFrameInputLoader(
          spark_session_factory, environment_helper, mocked_session
      )
  
      fg_name = tdh.INPUT_FEATURE_GROUP_NAME
      fg_data_source = FeatureGroupDataSource(name=fg_name)
      mock_input_loader.load_from_feature_group(fg_data_source)
  
      mocked_session.describe_feature_group.assert_called_with(fg_name)
      spark_session.table.assert_called_with(
          "awsdatacatalog.sagemaker_featurestore.input_fg_1680142547"
      )
  
imports: from __future__ import absolute_import
  import pytest
  import test_data_helpers
  from mock import Mock, patch, call
  from pyspark.sql import SparkSession, DataFrame
  from sagemaker.feature_store.feature_processor._data_source import CSVDataSource, FeatureGroupDataSource, ParquetDataSource, IcebergTableDataSource
  from sagemaker.feature_store.feature_processor._input_loader import SparkDataFrameInputLoader
  from sagemaker.feature_store.feature_processor._spark_factory import SparkSessionFactory
  from sagemaker.feature_store.feature_processor._env import EnvironmentHelper
  from sagemaker.session import Session
label_desc: Use image node_id 15 for calling a global function with example usage: test_load_from_feature_group_with_iceberg_table_format(describe_fg_response, spark_session_factory, spark_session, environment_helper) without return types