diff --git a/benchmark/paddle/image/plotlog.py b/benchmark/paddle/image/plotlog.py new file mode 100644 index 0000000000000000000000000000000000000000..9ac78d6910141854912cf63ec9384a247dee1852 --- /dev/null +++ b/benchmark/paddle/image/plotlog.py @@ -0,0 +1,87 @@ +#coding=utf-8 + +import sys +import argparse +import matplotlib.pyplot as plt + + +def parse_args(): + parser = argparse.ArgumentParser('Parse Log') + parser.add_argument( + '--file_path', '-f', type=str, help='the path of the log file') + parser.add_argument( + '--sample_rate', + '-s', + type=float, + default=1.0, + help='the rate to take samples from log') + parser.add_argument( + '--log_period', '-p', type=int, default=1, help='the period of log') + + args = parser.parse_args() + return args + + +def parse_file(file_name): + loss = [] + error = [] + with open(file_name) as f: + for i, line in enumerate(f): + line = line.strip() + if not line.startswith('pass'): + continue + line_split = line.split(' ') + if len(line_split) != 5: + continue + + loss_str = line_split[2][:-1] + cur_loss = float(loss_str.split('=')[-1]) + loss.append(cur_loss) + + err_str = line_split[3][:-1] + cur_err = float(err_str.split('=')[-1]) + error.append(cur_err) + + accuracy = [1.0 - err for err in error] + + return loss, accuracy + + +def sample(metric, sample_rate): + interval = int(1.0 / sample_rate) + if interval > len(metric): + return metric[:1] + + num = len(metric) / interval + idx = [interval * i for i in range(num)] + metric_sample = [metric[id] for id in idx] + return metric_sample + + +def plot_metric(metric, batch_id, graph_title): + plt.figure() + plt.title(graph_title) + plt.plot(batch_id, metric) + plt.xlabel('batch') + plt.ylabel(graph_title) + plt.savefig(graph_title + '.jpg') + plt.close() + + +def main(): + args = parse_args() + assert args.sample_rate > 0. and args.sample_rate <= 1.0, "The sample rate should in the range (0, 1]." + + loss, accuracy = parse_file(args.file_path) + batch = [args.log_period * i for i in range(len(loss))] + + batch_sample = sample(batch, args.sample_rate) + loss_sample = sample(loss, args.sample_rate) + accuracy_sample = sample(accuracy, args.sample_rate) + + plot_metric(loss_sample, batch_sample, 'loss') + plot_metric(accuracy_sample, batch_sample, 'accuracy') + + +if __name__ == '__main__': + main()