PyTorch_27_NeuralNetwork_ActivationFunctions.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "PyTorch_27_NeuralNetwork_ActivationFunctions.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOIqbigJSNrrIzU4tNMz09f",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/codeplinth/pytorchbootcamp/blob/master/PyTorch_27_NeuralNetwork_ActivationFunctions.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rc4uJKcoKKGS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "from torch import nn\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mBoD6aBWKXTo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "532639d8-6398-4026-fd3b-c8499aa099ed"
      },
      "source": [
        "torch.manual_seed(2)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<torch._C.Generator at 0x7faa00dd20d8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jAb3ELttKdve",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "z = torch.arange(-10,10,0.1).view(-1,1)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pobDj_thKkGf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sigmoid = nn.Sigmoid()"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ABPqDjNKKo-V",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y_pred = sigmoid(z)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6G6C8SlKKrne",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "outputId": "755d6ed7-85bf-4ff0-a102-22efefc30d36"
      },
      "source": [
        "plt.plot(z.detach().numpy(),y_pred.detach().numpy())\n",
        "plt.xlabel('z')\n",
        "plt.ylabel('y_pred')\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sXCMiUwLLPyW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tanh = nn.Tanh()"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bcTp7fBELme_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y_pred = tanh(z)"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iWDCEMfkLpU3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "outputId": "2afd9ab3-e7c5-4566-ab98-f57ee0855370"
      },
      "source": [
        "plt.plot(z.detach().numpy(),y_pred.detach().numpy())\n",
        "plt.xlabel('z')\n",
        "plt.ylabel('y_pred')\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CCsbcSuBLq3Q",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "relu = nn.ReLU()"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fYjWqH1YL1om",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y_pred = relu(z)"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OmSiwKImL4SO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "outputId": "eaac8872-e4e6-4dff-b5fd-12b64b98f54a"
      },
      "source": [
        "plt.plot(z.detach().numpy(),y_pred.detach().numpy())\n",
        "plt.xlabel('z')\n",
        "plt.ylabel('y_pred')\n",
        "plt.show()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hTiOhoPQL5a2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "outputId": "eeeaeb0f-e3a8-40a8-bc28-0b9ec4092678"
      },
      "source": [
        "z = torch.arange(-2,2,0.1).view(-1,1)\n",
        "plt.plot(z.detach().numpy(),sigmoid(z).detach().numpy(),label = 'Sigmoid')\n",
        "plt.plot(z.detach().numpy(),tanh(z).detach().numpy(),label = 'Tanh')\n",
        "plt.plot(z.detach().numpy(),relu(z).detach().numpy(),label = 'ReLU')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cBPs6VTQMQ-f",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}