code: def dump_plot(df, sizes):
      keys = []
      vals = []
      indexed = df[df["N"] == df["M"]]
      for index, row in indexed.iterrows():
          keys.append(row["name"])
          vals.append(row["ratio"])
  
      keys = keys[:: len(sizes)]
      sns.set(rc={"figure.figsize": (5.0, len(keys) * 0.5)})
  
      cmap = sns.diverging_palette(10, 120, n=9, as_cmap=True)
      np_vals = np.array([vals]).reshape(-1, len(sizes))
      g = sns.heatmap(
          np_vals, annot=True, cmap=cmap, center=1.0, yticklabels=True
      )
      plt.yticks(rotation=0)
      plt.title(
          "PyTorch performance divided by NNC performance (single core)"
      )
      plt.xlabel("Size of NxN matrix")
      plt.ylabel("Operation")
      g.set_yticklabels(keys)
      g.set_xticklabels(sizes)
  
      plt.savefig("nnc.png")
  
imports: import argparse
  import operator
  import time
  import matplotlib.pyplot
  import numpy
  import pandas
  import seaborn
  import torch
  import torch._C._te
label_desc: Use image node_id 12 for calling a global function with example usage: dump_plot(df, sizes) without return types