Datasets:
File size: 1,935 Bytes
89552cf | 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 | #!/usr/bin/env python3
"""Rename <task>-NNNN.parquet shards to the Hub convention data/train-XXXXX-of-YYYYY.parquet.
The Hub infers the split from this naming; without it load_dataset will not find
`train`. Renaming is an in-place os.rename, no data is copied.
Before renaming, every task in the meta file must have at least one shard. A
missing task means an export job failed silently, which is very hard to notice
after upload (the dataset looks normal, it just lacks a whole subset).
"""
import argparse, glob, json, os, re
ap = argparse.ArgumentParser()
ap.add_argument("--dir", default="parquet_out/data")
ap.add_argument("--meta", default="meta/meta_full.json")
ap.add_argument("--skip-completeness", action="store_true",
help="skip the every-task-has-a-shard check (only when exporting a subset on purpose)")
ap.add_argument("--apply", action="store_true", help="without this flag, only print the plan")
a = ap.parse_args()
files = sorted(f for f in glob.glob(os.path.join(a.dir, "*.parquet"))
if not re.match(r"train-\d{5}-of-\d{5}\.parquet$", os.path.basename(f)))
n = len(files)
if n == 0:
raise SystemExit("no shards to rename")
if not a.skip_completeness:
meta = json.load(open(a.meta))
have = {os.path.basename(f).rsplit("-", 1)[0] for f in files}
missing = sorted(set(meta) - have)
if missing:
raise SystemExit(
f"{len(missing)} task(s) have no shard; rerun them before finalizing:\n "
+ "\n ".join(missing))
total_b = sum(os.path.getsize(f) for f in files)
print(f"{n} shards, {total_b / 2**30:.1f} GiB in total")
for i, src in enumerate(files):
dst = os.path.join(a.dir, f"train-{i:05d}-of-{n:05d}.parquet")
if a.apply:
os.rename(src, dst)
elif i < 3 or i == n - 1:
print(f" {os.path.basename(src)} -> {os.path.basename(dst)}")
print("renamed" if a.apply else "(dry run; add --apply to rename)")
|