code: def __init__(self, args):
      self.args = args
      self.result_dict = defaultdict(
          lambda: {"bsz": [], "seq_len": [], "result": {}}
      )
  
      with open(self.args.csv_file, newline="") as csv_file:
          reader = csv.DictReader(csv_file)
          for row in reader:
              model_name = row["model"]
              self.result_dict[model_name]["bsz"].append(
                  int(row["batch_size"])
              )
              self.result_dict[model_name]["seq_len"].append(
                  int(row["sequence_length"])
              )
              if can_convert_to_int(row["result"]):
                  # value is not None
                  self.result_dict[model_name]["result"][
                      (
                          int(row["batch_size"]),
                          int(row["sequence_length"]),
                      )
                  ] = int(row["result"])
              elif can_convert_to_float(row["result"]):
                  # value is not None
                  self.result_dict[model_name]["result"][
                      (
                          int(row["batch_size"]),
                          int(row["sequence_length"]),
                      )
                  ] = float(row["result"])
  
file_path: transformers/examples/legacy/benchmarking/plot_csv_file.py
imports: import csv
  from collections import defaultdict
  from dataclasses import dataclass, field
  from typing import List, Optional
  import matplotlib.pyplot
  import numpy
  from matplotlib.ticker import ScalarFormatter
  from transformers import HfArgumentParser
label_desc: Use image node_id 1 to create a new Plot object  with example: obj = Plot(args)