0809

Author: 김민수

qtorch_1.ipynb

@@ -0,0 +1,134 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1. Using qtorch to tensor\n",
+    "\n",
+    "import torch\n",
+    "from qtorch.quant import Quantizer, quantizer\n",
+    "from qtorch import FloatingPoint"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[0.9562, 0.8024, 0.3401],\n",
+      "        [0.8613, 0.9098, 0.8928],\n",
+      "        [0.9854, 0.6158, 0.6871]])\n"
+     ]
+    }
+   ],
+   "source": [
+    "random_input = torch.rand([3,3])\n",
+    "print(random_input)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[ 255.0000, -255.0000],\n",
+      "        [   1.4000,    1.6000]])\n"
+     ]
+    }
+   ],
+   "source": [
+    "constant_input = torch.tensor([[255., -255.],[1.4, 1.6]])\n",
+    "print(constant_input)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set quantizer\n",
+    "bit = FloatingPoint(exp=2, man=1)\n",
+    "quant = quantizer(forward_number=bit, forward_rounding=\"nearest\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[1.0000, 0.7500, 0.5000],\n",
+      "        [0.7500, 1.0000, 1.0000],\n",
+      "        [1.0000, 0.5000, 0.7500]])\n"
+     ]
+    }
+   ],
+   "source": [
+    "random_output = quant(random_input)\n",
+    "print(random_output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[ 3.0000, -3.0000],\n",
+      "        [ 1.5000,  1.5000]])\n"
+     ]
+    }
+   ],
+   "source": [
+    "constant_output = quant(constant_input)\n",
+    "print(constant_output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}