code: def read_csv(csv_file, delimiter):
      cols = ["src", "dst", "val"]
      dtypes = OrderedDict(
          [
              ("src", "int32"),
              ("dst", "int32"),
              ("val", "float32"),
          ]
      )
  
      gdf = cudf.read_csv(
          csv_file,
          names=cols,
          delimiter=delimiter,
          dtype=list(dtypes.values()),
      )
  
      if gdf["src"].null_count > 0:
          print("The reader failed to parse the input")
      if gdf["dst"].null_count > 0:
          print("The reader failed to parse the input")
      # Assume an edge weight of 1.0 if dataset does not provide it
      if gdf["val"].null_count > 0:
          gdf["val"] = 1.0
      return gdf
  
file_path: cugraph/python/utils/run_benchmarks.py
imports: import argparse
  import sys
  from collections import OrderedDict
  from scipy.io import mmread
  import cugraph
  import cudf
  from benchmark import Benchmark
label_desc: Use image node_id 6 for calling a global function with example usage: read_csv(csv_file, delimiter) and returns: gdf