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31b85e0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import re
import pandas as pd
import matplotlib.pyplot as plt
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
from utils import get_analyzer, find_files
from arguments import parser
args = parser.parse_args()
if args.use_sns:
import seaborn as sns
sns.set()
def main():
target_affix = 'events.out.tfevents'
tb_log_paths = find_files(args.tb_dir, target_affix)
analyzer = get_analyzer(args.analyzer)
for tb_path in tb_log_paths:
print(f"Processing: {tb_path}")
analyzer.set_names(tb_path)
event_accumulator = EventAccumulator(tb_path)
event_accumulator.Reload()
events = event_accumulator.Scalars(args.tb_event_key)
x = [x.step for x in events]
y = [x.value for x in events]
plt.plot(x, y, label=f'{analyzer.get_label_name()}')
if not args.skip_csv:
df = pd.DataFrame({"step": x, "value": y})
df.to_csv(f"{args.csv_name}{analyzer.get_csv_filename()}.csv")
if not args.skip_plot:
plt.legend()
plt.title(args.plot_title)
plt.xlabel(args.plot_x_label)
plt.ylabel(args.plot_y_label)
plt.savefig(args.plot_name)
if __name__ == "__main__":
main()
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