code: def get_type_schema(path):
      format = path.split(".")[-1]
  
      if format == "parquet":
          return SchemaFrom.ParquetFile
      elif (
          format == "csv" or format == "psv" or format.startswith("txt")
      ):
          return SchemaFrom.CsvFile
  
imports: import time
  from collections import OrderedDict
  import numpy
  import pandas
  import pyblazing
  from pyblazing import DriverType, FileSystemType, SchemaFrom, get_dtype_values
  from sklearn.model_selection import train_test_split
  import xgboost
  from Configuration import Settings
  from DemoTest.chronometer import Chronometer
  from Utils import Execution
label_desc: Use image node_id 5 for calling a global function with example usage: get_type_schema(path) and returns: SchemaFrom, SchemaFrom