code: def test_load_from_feature_group_with_arn(
      mock_load_from_date_partitioned_s3,
      sagemaker_session,
      input_loader,
  ):
      fg_arn = tdh.INPUT_FEATURE_GROUP_ARN
      fg_name = tdh.INPUT_FEATURE_GROUP_NAME
      fg_data_source = FeatureGroupDataSource(
          name=fg_arn,
          input_start_offset="start",
          input_end_offset="end",
      )
  
      input_loader.load_from_feature_group(fg_data_source)
  
      sagemaker_session.describe_feature_group.assert_called_with(
          fg_name
      )
      mock_load_from_date_partitioned_s3.assert_called_with(
          ParquetDataSource(
              tdh.INPUT_FEATURE_GROUP_RESOLVED_OUTPUT_S3_URI
          ),
          "start",
          "end",
      )
  
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 12 for calling a global function with example usage: test_load_from_feature_group_with_arn(mock_load_from_date_partitioned_s3, sagemaker_session, input_loader) without return types