Pytorch_Basic_Introduction.ipynb

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  "metadata": {
    "colab": {
      "name": "Pytorch Basic Introduction.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMbkBWNzNAyNv9z6QdpHyfB",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ashishpatel26/Pytorch-Learning-/blob/main/Pytorch_Basic_Introduction.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hnMPSbsDHEsk"
      },
      "source": [
        "\r\n",
        "## Pytorch Introduction\r\n",
        "---\r\n",
        "PyTorch is an open source machine learning library for Python, based on Torch,used for applications such as natural language processing.It is primarily developed by Facebook's artificial-intelligence research group, and Uber's \"Pyro\" software for probabilistic programming is built on it.\r\n",
        "\r\n",
        "**PyTorch provides two high-level features:**\r\n",
        "* Tensor computation (like NumPy) with strong GPU, TPU Support\r\n",
        "* Deep Neural Networks built on a tape-based autodiff system\r\n",
        "\r\n",
        "---\r\n",
        "Environment Configuration\r\n",
        "---\r\n",
        "![PytorchInstallation.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0PIGGM0TJpeq"
      },
      "source": [
        "* [Step by Step Pytorch Installation Walkthrough on Windows](https://www.superdatascience.com/blogs/pytorch-windows-installation-walkthrough)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2lL_PvHDKToy"
      },
      "source": [
        "## Cuda Version Check"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fFs4muHGGxl_",
        "outputId": "b2015f77-dd5b-40c2-9a62-cb73c0222b3f"
      },
      "source": [
        "!nvcc --version"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2019 NVIDIA Corporation\n",
            "Built on Sun_Jul_28_19:07:16_PDT_2019\n",
            "Cuda compilation tools, release 10.1, V10.1.243\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ywWetaNAKLY2"
      },
      "source": [
        "## Installation of Pytorch"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_gHIqfHlIxQG",
        "outputId": "12488db9-ff84-4fd8-ec47-5f085aaa5b00"
      },
      "source": [
        "!pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Requirement already satisfied: torch==1.7.1+cu101 in /usr/local/lib/python3.6/dist-packages (1.7.1+cu101)\n",
            "Requirement already satisfied: torchvision==0.8.2+cu101 in /usr/local/lib/python3.6/dist-packages (0.8.2+cu101)\n",
            "Requirement already satisfied: torchaudio==0.7.2 in /usr/local/lib/python3.6/dist-packages (0.7.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (1.19.5)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (3.7.4.3)\n",
            "Requirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from torch==1.7.1+cu101) (0.8)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.6/dist-packages (from torchvision==0.8.2+cu101) (7.0.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yBvJNOarL4Gt",
        "outputId": "48acb86c-ea40-4c40-82b0-05b3421a2dda"
      },
      "source": [
        "import torch\r\n",
        "print(torch.__version__)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.7.1+cu101\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}