{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting copy with 48 processes...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Copying files: 100%|██████████| 7680/7680 [00:12<00:00, 626.66it/s]\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import shutil\n",
    "from multiprocessing import Pool\n",
    "from pathlib import Path\n",
    "from tqdm import tqdm\n",
    "\n",
    "def copy_file(args):\n",
    "    src, dst = args\n",
    "    os.makedirs(os.path.dirname(dst), exist_ok=True)\n",
    "    shutil.copy2(src, dst)\n",
    "    return src\n",
    "\n",
    "def parallel_copy():\n",
    "    # Source and destination paths\n",
    "    src_dir = \"/l/users/chaimaa.abi/all_code_thesis/finetune-DM/dataset_upscaled/upscaled_VLCS\"\n",
    "    dst_dir = \"/l/users/sarim.hashmi/Thesis/ICCV/chimaa_data/upscaled_VLCS\"\n",
    "    \n",
    "    # Get all files from source directory\n",
    "    src_files = []\n",
    "    dst_files = []\n",
    "    \n",
    "    for root, _, files in os.walk(src_dir):\n",
    "        for file in files:\n",
    "            src_path = os.path.join(root, file)\n",
    "            # Create corresponding destination path\n",
    "            rel_path = os.path.relpath(src_path, src_dir)\n",
    "            dst_path = os.path.join(dst_dir, rel_path)\n",
    "            \n",
    "            src_files.append(src_path)\n",
    "            dst_files.append(dst_path)\n",
    "    \n",
    "    # Create file pairs for mapping\n",
    "    file_pairs = list(zip(src_files, dst_files))\n",
    "    \n",
    "    # Create destination directory\n",
    "    os.makedirs(dst_dir, exist_ok=True)\n",
    "    \n",
    "    # Use Process Pool for parallel copying\n",
    "    num_processes = os.cpu_count()  # Use all available CPU cores\n",
    "    print(f\"Starting copy with {num_processes} processes...\")\n",
    "    \n",
    "    with Pool(num_processes) as pool:\n",
    "        # Use tqdm to show progress\n",
    "        for _ in tqdm(pool.imap_unordered(copy_file, file_pairs), \n",
    "                     total=len(file_pairs),\n",
    "                     desc=\"Copying files\"):\n",
    "            pass\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    parallel_copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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