Datasets:
File size: 2,909 Bytes
cfe406c | 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 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | #!/usr/bin/env python3
"""Tokenize the corpus with the Polish BPE into modded-nanogpt/llm.c shards.
Single process: tokenizers' encode_batch parallelises across cores via Rust rayon
natively — NO mp.Pool (nesting mp.Pool x rayon oversubscribes and is ~4x slower).
Format: 256 int32 header [magic 20240520, version 1, ntok] + uint16 tokens.
Docs joined with <|endoftext|>; ~1/200 docs held out for validation."""
import glob, os, time
import numpy as np
import pyarrow.parquet as pq
from tokenizers import Tokenizer
TOKJSON = "/home/ubuntu/dynaword/polish_bpe_32k.json"
DATA = "/home/ubuntu/dynaword/data"
OUT = "/home/ubuntu/dynaword/shards"
SHARD = 100_000_000
VAL_EVERY = 200
CHUNK = 50_000 # docs per encode_batch call
os.makedirs(OUT, exist_ok=True)
def doc_stream():
for f in sorted(glob.glob(f"{DATA}/*/*.parquet")):
for b in pq.ParquetFile(f).iter_batches(columns=["text"], batch_size=2000):
for x in b.column("text"):
s = x.as_py()
if s:
yield s
def write_shard(path, arr):
h = np.zeros(256, dtype=np.int32); h[0] = 20240520; h[1] = 1; h[2] = len(arr)
with open(path, "wb") as f:
f.write(h.tobytes()); f.write(arr.tobytes())
def main():
tok = Tokenizer.from_file(TOKJSON)
EOT = tok.token_to_id("<|endoftext|>")
print(f"EOT={EOT} | shard={SHARD:,} | val 1/{VAL_EVERY} | chunk={CHUNK}", flush=True)
buf = np.empty(SHARD + 2_000_000, dtype=np.uint16); tn = 0; sidx = 0
val = []
di = 0; total = 0; t0 = time.time()
chunk = []
def flush_chunk():
nonlocal tn, sidx, di, total
if not chunk:
return
for e in tok.encode_batch(chunk): # rayon -> all cores, single process
ids = e.ids
# EOT PREFIX (BOS before each doc) -> matches modded-nanogpt align_to_bos
if di % VAL_EVERY == 0:
val.append(EOT); val.extend(ids)
else:
buf[tn] = EOT; tn += 1
m = len(ids)
buf[tn:tn+m] = ids; tn += m
if tn >= SHARD:
write_shard(f"{OUT}/polish_train_{sidx:06d}.bin", buf[:tn])
total += tn; sidx += 1; tn = 0
di += 1
chunk.clear()
print(f" {di:,} docs | {(total+tn)/1e9:.2f}B train tok | {len(val)/1e6:.1f}M val | {time.time()-t0:.0f}s", flush=True)
for s in doc_stream():
chunk.append(s)
if len(chunk) >= CHUNK:
flush_chunk()
flush_chunk()
if tn:
write_shard(f"{OUT}/polish_train_{sidx:06d}.bin", buf[:tn]); total += tn; sidx += 1
write_shard(f"{OUT}/polish_val_000000.bin", np.array(val, dtype=np.uint16))
print(f"\nDONE: {sidx} train shards, {total:,} train tok, {len(val):,} val tok | "
f"{di:,} docs | {time.time()-t0:.0f}s", flush=True)
if __name__ == "__main__":
main()
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