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#!/usr/bin/env python3
import glob
import os
import re
import tensorflow as tf
from torch.utils.tensorboard import SummaryWriter
GROUPING_RULES = [
re.compile(r'^(?P<group>train|test|val|extra_val_.*?(256|512))_(?P<title>.*)', re.I)
]
DROP_RULES = [
re.compile(r'_std$', re.I)
]
def need_drop(tag):
for rule in DROP_RULES:
if rule.search(tag):
return True
return False
def get_group_and_title(tag):
for rule in GROUPING_RULES:
match = rule.search(tag)
if match is None:
continue
return match.group('group'), match.group('title')
return None, None
def main(args):
os.makedirs(args.outdir, exist_ok=True)
ignored_events = set()
for orig_fname in glob.glob(args.inglob):
cur_dirpath = os.path.dirname(orig_fname) # remove filename, this should point to "version_0" directory
subdirname = os.path.basename(cur_dirpath) # == "version_0" most of time
exp_root_path = os.path.dirname(cur_dirpath) # remove "version_0"
exp_name = os.path.basename(exp_root_path)
writers_by_group = {}
for e in tf.compat.v1.train.summary_iterator(orig_fname):
for v in e.summary.value:
if need_drop(v.tag):
continue
cur_group, cur_title = get_group_and_title(v.tag)
if cur_group is None:
if v.tag not in ignored_events:
print(f'WARNING: Could not detect group for {v.tag}, ignoring it')
ignored_events.add(v.tag)
continue
cur_writer = writers_by_group.get(cur_group, None)
if cur_writer is None:
if args.include_version:
cur_outdir = os.path.join(args.outdir, exp_name, f'{subdirname}_{cur_group}')
else:
cur_outdir = os.path.join(args.outdir, exp_name, cur_group)
cur_writer = SummaryWriter(cur_outdir)
writers_by_group[cur_group] = cur_writer
cur_writer.add_scalar(cur_title, v.simple_value, global_step=e.step, walltime=e.wall_time)
if __name__ == '__main__':
import argparse
aparser = argparse.ArgumentParser()
aparser.add_argument('inglob', type=str)
aparser.add_argument('outdir', type=str)
aparser.add_argument('--include-version', action='store_true',
help='Include subdirectory name e.g. "version_0" into output path')
main(aparser.parse_args())
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