code: def make_ds(size_gb: int, parallelism: int = -1):
      # Dataset of 10KiB tensor records.
      total_size = 1024 * 1024 * 1024 * size_gb
      record_dim = 1024
      record_size = record_dim * 8
      num_records = int(total_size / record_size)
      dataset = ray.data.range_tensor(
          num_records, shape=(record_dim,), parallelism=parallelism
      )
      print("Created dataset", dataset, "of size", dataset.size_bytes())
      return dataset
  
file_path: ray/release/nightly_tests/dataset/data_ingest_benchmark.py
imports: import numpy
  import sys
  import time
  import argparse
  from benchmark import Benchmark
  import ray
  from ray.data import Dataset
  from ray.data import DatasetPipeline
  import pandas
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: make_ds(size_gb, parallelism) and returns: dataset