code: def get_memory_statistics(allocation_counts, input_memory):
      """
      Get memory statistics for the benchmark.
      """
      output_to_peak_ratio = get_peak_output_ratio_across_workers(
          allocation_counts
      )
      peak_allocation_across_workers = max(
          [a["peak_bytes"] for a in allocation_counts.values()]
      )
      input_memory_per_worker = input_memory / len(
          allocation_counts.keys()
      )
      input_to_peak_ratio = (
          peak_allocation_across_workers / input_memory_per_worker
      )
      print(f"Edge List Memory = {sizeof_fmt(input_memory_per_worker)}")
      print(
          f"Peak Memory across workers = {sizeof_fmt(peak_allocation_across_workers)}"
      )
      print(
          f"Max Peak to output graph ratio across workers = {output_to_peak_ratio:.2f}"
      )
      print(
          f"Max Peak to avg input graph ratio across workers = {input_to_peak_ratio:.2f}"
      )
      return (
          input_to_peak_ratio,
          output_to_peak_ratio,
          input_memory_per_worker,
          peak_allocation_across_workers,
      )
  
file_path: cugraph/benchmarks/cugraph/standalone/cugraph_graph_creation.py
imports: from cugraph.testing.mg_utils import generate_edgelist_rmat, get_allocation_counts_dask_persist, get_allocation_counts_dask_lazy, sizeof_fmt, get_peak_output_ratio_across_workers, restart_client
  from cugraph.testing.mg_utils import start_dask_client, stop_dask_client, enable_spilling
  from cugraph.structure.symmetrize import symmetrize_ddf
  import cugraph
  import cudf
  from time import sleep
  import pandas
  import time
label_desc: Use image node_id 5 for calling a global function with example usage: get_memory_statistics(allocation_counts, input_memory) and returns: input_to_peak_ratio,  output_to_peak_ratio,  input_memory_per_worker,  peak_allocation_across_workers