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analyser.ipynb

@@ -0,0 +1,115 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading parquet files...\n",
+      "Processing dataframes...\n",
+      "\n",
+      "Merging dataframes...\n",
+      "\n",
+      "Formatting output...\n",
+      "\n",
+      "Total pairs found: 216775\n",
+      "\n",
+      "Saving to parquet file...\n",
+      "\n",
+      "Sample pairs:\n",
+      "                                   hip_filename  \\\n",
+      "0  fcd394853732933cc2ddcf59fa29d561f0263cb1.hip   \n",
+      "1  d654bdeca448d1a413a7cc87ccc3b4b7f18a965d.hip   \n",
+      "2  464e3d1584f0013dfda51116d9aaaf21bd91bc13.hip   \n",
+      "3  21a2390523ec5438ddf21ad9d91b04ae044ec944.hip   \n",
+      "4  2b375ca1064061439fdc87fb32d664cc9434d26e.hip   \n",
+      "\n",
+      "                                 cuda_filename  \n",
+      "0  fcd394853732933cc2ddcf59fa29d561f0263cb1.cu  \n",
+      "1  d654bdeca448d1a413a7cc87ccc3b4b7f18a965d.cu  \n",
+      "2  464e3d1584f0013dfda51116d9aaaf21bd91bc13.cu  \n",
+      "3  21a2390523ec5438ddf21ad9d91b04ae044ec944.cu  \n",
+      "4  2b375ca1064061439fdc87fb32d664cc9434d26e.cu  \n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import multiprocessing as mp\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "def create_paired_dataset(cuda_df, hip_df):\n",
+    "    print(\"Processing dataframes...\")\n",
+    "    \n",
+    "    # Create base names for both dataframes at once\n",
+    "    cuda_df['base_name'] = cuda_df['filename'].str.replace(r'\\.cu[h]?$', '', regex=True)\n",
+    "    hip_df['base_name'] = hip_df['filename'].str.replace(r'\\.hip$', '', regex=True)\n",
+    "    \n",
+    "    # Merge dataframes on base_name - this is much faster than iterative matching\n",
+    "    print(\"\\nMerging dataframes...\")\n",
+    "    paired_df = pd.merge(\n",
+    "        hip_df,\n",
+    "        cuda_df,\n",
+    "        on='base_name',\n",
+    "        suffixes=('_hip', '_cuda')\n",
+    "    )\n",
+    "    \n",
+    "    # Rename columns to match desired output format\n",
+    "    print(\"\\nFormatting output...\")\n",
+    "    result_df = pd.DataFrame({\n",
+    "        'hip_filename': paired_df['filename_hip'],\n",
+    "        'hip_content': paired_df['content_hip'],\n",
+    "        'cuda_filename': paired_df['filename_cuda'],\n",
+    "        'cuda_content': paired_df['content_cuda']\n",
+    "    })\n",
+    "    \n",
+    "    print(f\"\\nTotal pairs found: {len(result_df)}\")\n",
+    "    \n",
+    "    print(\"\\nSaving to parquet file...\")\n",
+    "    result_df.to_parquet('cuda_hip_paired.parquet')\n",
+    "    \n",
+    "    print(\"\\nSample pairs:\")\n",
+    "    print(result_df[['hip_filename', 'cuda_filename']].head())\n",
+    "    return result_df\n",
+    "\n",
+    "if __name__ == '__main__':\n",
+    "    print(\"Reading parquet files...\")\n",
+    "    cuda_df = pd.read_parquet('cuda_files.parquet')\n",
+    "    hip_df = pd.read_parquet('hip_files.parquet')\n",
+    "    create_paired_dataset(cuda_df, hip_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llava_med_v2",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

cuda_files.parquet → cuda_hip_paired.parquet

@@ -1,3 +1,3 @@
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-oid sha256:c64223701c19833cec99551fd4e28fb8c19bb6aad68b0c3f845dcaaa9f5b8d8f
-size 1134434699
+oid sha256:ccba7eb2a3a187a91e2ad357e1dd046196ac7b96c937e46d7c268b9e0e99c657
+size 1586032761

hip_files.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3bedf88ae379cbde2135813f32d03831793d404a94eff50b65a5e87574ade1a5
-size 795970240