code: def test_load_from_s3_with_csv_object(
      input_loader: SparkDataFrameInputLoader, spark_session
  ):
      s3_data_source = CSVDataSource(
          s3_uri="s3://bucket/prefix/file.csv",
          csv_header=True,
          csv_infer_schema=True,
      )
  
      input_loader.load_from_s3(s3_data_source)
  
      spark_session.read.csv.assert_called_with(
          "s3a://bucket/prefix/file.csv", header=True, inferSchema=True
      )
  
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 9 for calling a global function with example usage: test_load_from_s3_with_csv_object(input_loader, spark_session) without return types