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使用 Colaboratory 建立
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‎pytorch_tutorial.ipynb

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"authorship_tag": "ABX9TyOPTFE36tjCuSWE+KQiRFpr",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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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/CodingCoffee-01/python_tutorial/blob/master/pytorch_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"id": "OmyiwdFQTR6G"
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},
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"outputs": [],
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"source": [
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"import torch\n",
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"\n",
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"# Create a tensor\n",
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"x = torch.tensor([1, 2, 3])"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"# Dynamic computation\n",
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"y = x + 2\n",
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"z = y * 3\n",
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"\n",
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"print(\"x=\",x)\n",
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"print(\"y=\",y)\n",
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"print(\"z=\",z)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "Ju82isbuTlAX",
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"outputId": "29cec62a-ebc1-4587-ec94-ef0d91bb8d1f"
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},
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"execution_count": 6,
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"outputs": [
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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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"x= tensor([1, 2, 3])\n",
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"y= tensor([3, 4, 5])\n",
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"z= tensor([ 9, 12, 15])\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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"source": [
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"# importing torch\n",
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"import torch\n",
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"\n",
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"# creating a tensors\n",
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"t1=torch.tensor([1, 2, 3, 4])\n",
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"t2=torch.tensor([[1, 2, 3, 4],\n",
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" [5, 6, 7, 8],\n",
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" [9, 10, 11, 12]])\n",
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"\n",
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"# printing the tensors:\n",
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"print(\"Tensor t1: \\n\", t1)\n",
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"print(\"\\nTensor t2: \\n\", t2)\n",
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"\n",
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"# rank of tensors\n",
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"print(\"\\nRank of t1: \", len(t1.shape))\n",
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"print(\"Rank of t2: \", len(t2.shape))\n",
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"\n",
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"# shape of tensors\n",
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"print(\"\\nRank of t1: \", t1.shape)\n",
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"print(\"Rank of t2: \", t2.shape)\n",
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"\n",
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"print(\"t1+3 :\",t1+3)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "byu2p9kRURl6",
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"outputId": "d26fc4c6-7ed3-426f-ab7b-7b43e82fbd76"
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},
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"execution_count": 5,
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"outputs": [
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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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"Tensor t1: \n",
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" tensor([1, 2, 3, 4])\n",
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"\n",
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"Tensor t2: \n",
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" tensor([[ 1, 2, 3, 4],\n",
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" [ 5, 6, 7, 8],\n",
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" [ 9, 10, 11, 12]])\n",
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"\n",
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"Rank of t1: 1\n",
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"Rank of t2: 2\n",
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"\n",
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"Rank of t1: torch.Size([4])\n",
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"Rank of t2: torch.Size([3, 4])\n",
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"t1+3 : tensor([4, 5, 6, 7])\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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}

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