evanfrick commited on
Commit
5c07e1a
1 Parent(s): d978a55

converted to parquet

Browse files
data/{lichess_game_data.txt → lichess_data.parquet} RENAMED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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extra/chess_game_data.txt DELETED
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extra/fix.ipynb ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import pandas as pd\n",
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+ "import json\n",
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+ "import jsonlines\n"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "\n",
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+ "with jsonlines.open('lichess_data.jsonl', 'a') as writer:\n",
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+ " with open(\"lichess_game_data.txt\", 'r') as readf:\n",
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+ " line = readf.readline()\n",
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+ " count = 0\n",
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+ " while line:\n",
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+ " data_line = {'id': count, 'pgn': line}\n",
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+ " writer.write(data_line)\n",
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+ " line = readf.readline()\n",
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+ " count += 1"
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "chess",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.11.5"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 2
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+ }
extra/test_dataset.ipynb DELETED
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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "s:\\packages\\envs\\chess\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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- " from .autonotebook import tqdm as notebook_tqdm\n"
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- ]
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- }
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- ],
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- "source": [
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- "from datasets import load_dataset\n",
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- "import tokenize\n",
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- "from tokenizers import SentencePieceBPETokenizer, pre_tokenizers, ByteLevelBPETokenizer, normalizers\n",
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- "from transformers import AutoTokenizer"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 132,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "Downloading data files: 100%|██████████| 1/1 [00:00<?, ?it/s]\n",
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- "Extracting data files: 100%|██████████| 1/1 [00:00<00:00, 111.41it/s]\n",
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- "Generating train split: 4343360 examples [00:24, 178753.60 examples/s]\n"
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- ]
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- }
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- ],
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- "source": [
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- "datasets = load_dataset(\"text\", data_files={\"train\": \"lichess_game_data.txt\"})"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 133,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "def get_training_corpus():\n",
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- " dataset = datasets[\"train\"]\n",
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- " for start_idx in range(0, len(dataset), 1000):\n",
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- " samples = dataset[start_idx : start_idx + 1000]\n",
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- " yield samples['text']"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 134,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "tokenizer = SentencePieceBPETokenizer()"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 135,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "tokenizer.normalizer = normalizers.Sequence([normalizers.Replace(\".\", \"\"), normalizers.Replace(\"1-0\", \"\"), normalizers.Replace(\"0-1\", \"\"), normalizers.Replace(\"1/2-1/2\", \"\")])"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 136,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "tokenizer.pre_tokenizer = pre_tokenizers.Split(\" \", 'removed')"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 137,
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- "metadata": {},
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- "outputs": [],
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- "source": [
89
- "tokenizer.train_from_iterator(get_training_corpus(), vocab_size=10000000, min_frequency=0, show_progress=True, special_tokens=[\"<s>\", \"<pad>\", \"</s>\", \"<unk>\", \"<cls>\", \"<sep>\", \"<mask>\"])"
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- {
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- "cell_type": "code",
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- "execution_count": 138,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "test_str = '1. e4 e5 2. Nf3 Nc6 3. d4 exd4 4. Nxd4 Nf6 5. Nxc6 bxc6 6. Bd3 d5 7. exd5 cxd5 8. O-O Be7 9. c4 O-O 10. cxd5 Bb7 11. Nc3 Nxd5 12. Bd2 Nb4 13. Be4 Bxe4 14. Nxe4 c5 15. Bc3 Qxd1 16. Rfxd1 Rad8 17. a3 Nd5 18. Ba5 Nb6 19. Nc3 Bf6 20. Rac1 Bxc3 21. Bxc3 Rxd1+ 22. Rxd1 f6 23. Kf1 Kf7 24. Rc1 Rd8 25. Ke2 Ke6 26. Bd2 c4 27. Be3 Rb8 28. Rc2 Rb7 29. h3 Kd5 30. Rd2+ Ke6 31. Rd4 a5 32. g3 Nd5 33. Bc1 Nb6 34. h4 g6 35. Bd2 Nd5 36. Bc1 Nb6 37. Bd2 Nd5 38. Rxc4 Rxb2 39. Ke1 Nb6 40. Re4+ Kd5 41. Re7 Rb1+ 42. Ke2 Nc4 43. Bc3 f5 44. Rd7+ Ke6 45. Rxh7 Rb3 46. Bd4 Rxa3 47. Rc7 Ra2+ 48. Kf3 Kd5 49. Rd7+ Kc6 50. Rg7 Kd5 51. Rd7+ Kc6 52. Rg7 Kd5 53. Rd7+ 1/2-1/2'"
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- ]
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- " 'Rd7+',\n",
432
- " 'Kc6',\n",
433
- " '50',\n",
434
- " 'Rg7',\n",
435
- " 'Kd5',\n",
436
- " '51',\n",
437
- " 'Rd7+',\n",
438
- " 'Kc6',\n",
439
- " '52',\n",
440
- " 'Rg7',\n",
441
- " 'Kd5',\n",
442
- " '53',\n",
443
- " 'Rd7+']"
444
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445
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446
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447
- "metadata": {},
448
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449
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450
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451
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452
- "tokenizer.encode(test_str).tokens"
453
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454
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455
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456
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457
- "execution_count": 142,
458
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459
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506
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521
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523
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524
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570
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
- "cell_type": "code",
634
- "execution_count": 143,
635
- "metadata": {},
636
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638
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639
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643
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644
- "metadata": {},
645
- "output_type": "execute_result"
646
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647
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648
- "source": [
649
- "tokenizer.get_vocab_size()"
650
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651
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652
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653
- "cell_type": "code",
654
- "execution_count": null,
655
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656
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660
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664
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669
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