mirror of
https://github.com/dantetemplar/pdf-extraction-agenda.git
synced 2025-03-17 21:12:24 +03:00
1711 lines
59 KiB
Plaintext
1711 lines
59 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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||
"<a href=\"https://colab.research.google.com/github/dantetemplar/pdf-extraction-agenda/blob/main/repack_olmOCR_mix_0225.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"### This script extract eval from [olmOCR dataset](https://huggingface.co/datasets/allenai/olmOCR-mix-0225) and repack it to reduce download time"
|
||
],
|
||
"metadata": {
|
||
"id": "74Lyc5fiLRie"
|
||
}
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"!pip install -q datasets huggingface-hub[hf-transfer]"
|
||
],
|
||
"metadata": {
|
||
"id": "rTSLld0eIBSQ",
|
||
"collapsed": true
|
||
},
|
||
"execution_count": 7,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"import json\n",
|
||
"import os\n",
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||
"\n",
|
||
"from datasets import load_dataset\n",
|
||
"from huggingface_hub import snapshot_download\n",
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||
"\n",
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||
"\n",
|
||
"def download_files():\n",
|
||
" os.environ[\"HF_HUB_ENABLE_HF_TRANSFER\"] = \"1\"\n",
|
||
" path_to_snaphot = snapshot_download(repo_id=\"allenai/olmOCR-mix-0225\", repo_type=\"dataset\", allow_patterns=[\"*.tar.gz\"])\n",
|
||
" return path_to_snaphot"
|
||
],
|
||
"metadata": {
|
||
"id": "9i21u_7QRVB_"
|
||
},
|
||
"execution_count": 8,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"dataset = load_dataset(\"allenai/olmOCR-mix-0225\", \"00_documents\", split=\"eval_s2pdf\")"
|
||
],
|
||
"metadata": {
|
||
"id": "KsMlhISsRZA1"
|
||
},
|
||
"execution_count": 9,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"path_to_snaphot = download_files()"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
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||
"height": 49,
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"referenced_widgets": [
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"c0862d5ded6e4c2d9b07a1d450c46dd5",
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"4fc45801eaed4dd1bf3f629ff111c8d3",
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"8ffa244f284842f5bde7f969e4c94db6",
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]
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},
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"id": "Zub4qMHqReHr",
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"outputId": "23354ab7-ce7a-47ca-f646-e47717bb9346",
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"collapsed": true
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},
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||
"execution_count": 10,
|
||
"outputs": [
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Fetching 52 files: 0%| | 0/52 [00:00<?, ?it/s]"
|
||
],
|
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"application/vnd.jupyter.widget-view+json": {
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"version_major": 2,
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"version_minor": 0,
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"model_id": "c0862d5ded6e4c2d9b07a1d450c46dd5"
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}
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},
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"metadata": {}
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}
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]
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},
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||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"import tarfile\n",
|
||
"\n",
|
||
"from collections import Counter\n",
|
||
"from tqdm import tqdm\n",
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||
"\n",
|
||
"ids = dataset.select_columns([\"id\"]).to_list()\n",
|
||
"id_set = {id_dict[\"id\"] + \".pdf\" for id_dict in ids}\n",
|
||
"pdf_tarballs_dir = f\"{path_to_snaphot}/pdf_tarballs\"\n",
|
||
"tar_files = [os.path.join(pdf_tarballs_dir, f) for f in os.listdir(pdf_tarballs_dir) if f.endswith(\".tar.gz\")]\n",
|
||
"\n",
|
||
"counter = Counter()\n",
|
||
"extracted_files = {}\n",
|
||
"temp_extract_dir = \"temp_extracted\"\n",
|
||
"\n",
|
||
"os.makedirs(temp_extract_dir, exist_ok=True)\n",
|
||
"\n",
|
||
"for tarball_path in tqdm(tar_files):\n",
|
||
" with tarfile.open(tarball_path, \"r:gz\") as tar:\n",
|
||
" for member in tar.getmembers():\n",
|
||
" if member.name in id_set: # Only extract relevant PDFs\n",
|
||
" tar.extract(member, path=temp_extract_dir)\n",
|
||
" extracted_files[member.name] = os.path.join(temp_extract_dir, member.name)\n",
|
||
" counter[tarball_path] += 1\n",
|
||
"\n",
|
||
"print(f\"Extracted {len(extracted_files)} PDFs.\")"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "blH_w2dWeq1O",
|
||
"outputId": "183b01ea-6bc9-4631-d56b-1c9ef662d416"
|
||
},
|
||
"execution_count": 12,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stderr",
|
||
"text": [
|
||
"100%|██████████| 52/52 [13:32<00:00, 15.62s/it]"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Extracted 1166 PDFs.\n"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stderr",
|
||
"text": [
|
||
"\n"
|
||
]
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||
}
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||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"assert all([extracted_files.get(id_) for id_ in id_set]), \"All files should be extracted\"\n",
|
||
"print(f\"Relevant pdfs was distributed into {len(counter)} tarballs originally\")"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "BSembq8pckZQ",
|
||
"outputId": "83c42461-91e7-44c2-e8ff-a71325e71714"
|
||
},
|
||
"execution_count": 13,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Relevant pdfs was distributed into 49 tarballs originally\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"target_chunk_size = 1 * 1024**3 # 1GB in bytes\n",
|
||
"chunks = []\n",
|
||
"current_chunk = []\n",
|
||
"current_size = 0\n",
|
||
"total_size = 0\n",
|
||
"\n",
|
||
"for pdf_name, pdf_path in extracted_files.items():\n",
|
||
" file_size = os.path.getsize(pdf_path)\n",
|
||
" if current_size + file_size > target_chunk_size and current_chunk:\n",
|
||
" chunks.append(current_chunk)\n",
|
||
" current_chunk = []\n",
|
||
" current_size = 0\n",
|
||
"\n",
|
||
" current_chunk.append((pdf_name, pdf_path))\n",
|
||
" current_size += file_size\n",
|
||
" total_size += file_size\n",
|
||
"\n",
|
||
"if current_chunk:\n",
|
||
" chunks.append(current_chunk)\n",
|
||
"print(f\"Will be {len(chunks)} chunks. Total {total_size / (1 * 1024 ** 3):.2f} GB\")"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
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||
"id": "wuE5RSJMfmfD",
|
||
"outputId": "2896e7a4-aa74-43a6-afb8-dfe55bb169c5"
|
||
},
|
||
"execution_count": 14,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Will be 1 chunks. Total 0.20 GB\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"output_dir = \"new_tarballs\"\n",
|
||
"os.makedirs(output_dir, exist_ok=True)\n",
|
||
"new_tarballs = []\n",
|
||
"\n",
|
||
"for i, chunk in enumerate(chunks):\n",
|
||
" tarball_path = os.path.join(output_dir, f\"pdf_chunk_{i:04d}.tar.gz\")\n",
|
||
" with tarfile.open(tarball_path, \"w:gz\") as tar:\n",
|
||
" for pdf_name, pdf_path in chunk:\n",
|
||
" tar.add(pdf_path, arcname=pdf_name)\n",
|
||
" new_tarballs.append(tarball_path)\n",
|
||
"\n",
|
||
"print(\"Tarballs packed, ready for upload.\")"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "NTYtwlcCf0iB",
|
||
"outputId": "3116d454-b0db-435a-9be3-5a128e523734"
|
||
},
|
||
"execution_count": 15,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Tarballs packed, ready for upload.\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"from huggingface_hub import notebook_login\n",
|
||
"\n",
|
||
"notebook_login()"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
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"height": 17,
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"referenced_widgets": [
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"93a4749b2bd54021a2dbb18c28cbff48",
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"id": "Pr2DA_0XnAZZ",
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"outputId": "d777a21b-6203-4582-86dd-6f3dbc32b437"
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},
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"execution_count": 16,
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"text/plain": [
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"VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
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],
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"application/vnd.jupyter.widget-view+json": {
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"version_major": 2,
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"version_minor": 0,
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"model_id": "93a4749b2bd54021a2dbb18c28cbff48"
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}
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},
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"metadata": {}
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}
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]
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},
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{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"from huggingface_hub import HfApi\n",
|
||
"import shutil\n",
|
||
"\n",
|
||
"api = HfApi()\n",
|
||
"repo_id = \"dantetemplar/pdf-extraction-agenda\"\n",
|
||
"\n",
|
||
"for tarball in new_tarballs:\n",
|
||
" api.upload_file(\n",
|
||
" path_or_fileobj=tarball,\n",
|
||
" path_in_repo=f\"data/olmOCR-mix-0225/{os.path.basename(tarball)}\",\n",
|
||
" repo_id=repo_id,\n",
|
||
" repo_type=\"dataset\"\n",
|
||
" )\n",
|
||
"\n",
|
||
"shutil.rmtree(temp_extract_dir)\n",
|
||
"print(\"Uploaded all new tarballs to Hugging Face!\")"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
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"base_uri": "https://localhost:8080/",
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"height": 66,
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"referenced_widgets": [
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},
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"execution_count": 18,
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"text/plain": [
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"pdf_chunk_0000.tar.gz: 0%| | 0.00/200M [00:00<?, ?B/s]"
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],
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},
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"metadata": {}
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},
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Uploaded all new tarballs to Hugging Face!\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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}
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],
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"metadata": {
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"colab": {
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"gpuType": "T4",
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"provenance": [],
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"authorship_tag": "ABX9TyOlcDSLMqc5q1z5kFtgDk6K",
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"include_colab_link": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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