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import argparse
import numpy as np
from matplotlib import pyplot as plt
def parse_args():
parser = argparse.ArgumentParser(
description="Plot losses from log")
parser.add_argument("--log-file", help="path to log file", required=True)
parser.add_argument("--fake-weight", help="weight for fake loss", default=1.4, type=float)
args = parser.parse_args()
return args
def main():
args = parse_args()
with open(args.log_file, "r") as f:
lines = f.readlines()
real_losses = []
fake_losses = []
for line in lines:
line = line.strip()
if line.startswith("fake_loss"):
fake_losses.append(float(line.split(" ")[-1]))
elif line.startswith("real_loss"):
real_losses.append(float(line.split(" ")[-1]))
real_losses = np.array(real_losses)
fake_losses = np.array(fake_losses)
loss = (fake_losses * args.fake_weight + real_losses)/2
plt.title("Weighted loss ({}*fake_loss + real_loss)/2)".format(args.fake_weight))
best_loss_idx = np.argsort(loss)[:5]
# ignore early epochs loss is quite noisy and there could be spikes
best_loss_idx = best_loss_idx[best_loss_idx > 16]
plt.scatter(best_loss_idx, loss[best_loss_idx], c="red")
for idx in best_loss_idx:
plt.annotate(str(idx), (idx, loss[idx]))
plt.plot(loss)
plt.show()
if __name__ == '__main__':
main()
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