Milvus integrated

Author: awarebayes

examples/1. Vanilla RL/2. DDPG.ipynb

@@ -0,0 +1,121 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/ssd/anaconda/envs/recnn/lib/python3.8/site-packages/tqdm/std.py:670: FutureWarning: The Panel class is removed from pandas. Accessing it from the top-level namespace will also be removed in the next version\n",
+      "  from pandas import Panel\n"
+     ]
+    }
+   ],
+   "source": [
+    "from milvus import Milvus, IndexType, MetricType, Status\n",
+    "\n",
+    "# == recnn ==\n",
+    "import sys\n",
+    "sys.path.append(\"../../../\")\n",
+    "import recnn"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "source": [
+    "\n",
+    "frame_size = 10\n",
+    "batch_size = 1\n",
+    "# embeddgings: https://drive.google.com/open?id=1EQ_zXBR3DKpmJR3jBgLvt-xoOvArGMsL\n",
+    "dirs = recnn.data.env.DataPath(\n",
+    "    base=\"../../../data/\",\n",
+    "    embeddings=\"embeddings/ml20_pca128.pkl\",\n",
+    "    ratings=\"ml-20m/ratings.csv\",\n",
+    "    cache=\"cache/frame_env.pkl\", # cache will generate after you run\n",
+    "    use_cache=True\n",
+    ")\n",
+    "env = recnn.data.env.FrameEnv(dirs, frame_size, batch_size)\n",
+    "\n",
+    "from recnn.data.db_con import MilvusConnection\n",
+    "milvus = MilvusConnection(env)\n",
+    "\n",
+    "import numpy as np\n",
+    "q_records = np.random.rand(3, 128)\n",
+    "\n",
+    "results = milvus.search(q_records)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "execution_count": 3,
+   "outputs": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "tensor([[21268,  1287, 23734, 22477, 19162, 14730,  1705, 22382, 14789, 18980],\n        [21268,  1287, 23734, 22477,  1705, 14730, 19162, 18980, 22382, 14789],\n        [21268,  1287, 23734, 22477, 19162, 14730,  1705, 22382, 14789, 22131]])"
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}