code: def get_len_vectors_per_file(data_type, dimension):
      if data_type == "random":
          if dimension == 512:
              vectors_per_file = VECTORS_PER_FILE
          elif dimension == 4096:
              vectors_per_file = 100000
          elif dimension == 16384:
              vectors_per_file = 10000
          else:
              raise Exception(
                  "dimension: %s not supported" % str(dimension)
              )
      elif data_type == "sift":
          vectors_per_file = SIFT_VECTORS_PER_FILE
      elif data_type in ["binary"]:
          vectors_per_file = BINARY_VECTORS_PER_FILE
      elif data_type == "local":
          vectors_per_file = SIFT_VECTORS_PER_FILE
      else:
          raise Exception("data_type: %s not supported" % data_type)
      return vectors_per_file
  
imports: import os
  import logging
  import numpy
  import sklearn.preprocessing
  import h5py
  import random
  from itertools import product
  from pymilvus import DataType
  from milvus_benchmark import config
label_desc: Use image node_id 1 for calling a global function with example usage: get_len_vectors_per_file(data_type, dimension) and returns: vectors_per_file