From a1084cac495a4762e4c646f4989bc02d62e729e0 Mon Sep 17 00:00:00 2001
From: Allen K Abraham <allen@theabstraction.co>
Date: Sat, 13 Jun 2020 15:41:03 +0530
Subject: [PATCH] Task 2

---
 Tasks/daily tasks/Allen K Abraham/task2.ipynb | 122 ++++++++++++++++++
 1 file changed, 122 insertions(+)
 create mode 100644 Tasks/daily tasks/Allen K Abraham/task2.ipynb

diff --git a/Tasks/daily tasks/Allen K Abraham/task2.ipynb b/Tasks/daily tasks/Allen K Abraham/task2.ipynb
new file mode 100644
index 0000000..9157f15
--- /dev/null
+++ b/Tasks/daily tasks/Allen K Abraham/task2.ipynb	
@@ -0,0 +1,122 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "task2.ipynb",
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "841adttKIgfL",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import torch.nn as nn\n",
+        "import torch"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7KbBAQjNIvdx",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "\n",
+        "class Network(nn.Module):\n",
+        "    def __init__(self,N_in,N_out):\n",
+        "        super(Network, self).__init__()\n",
+        "        self.input = nn.Linear(N_in, 400)\n",
+        "        self.fc1 = nn.Linear(400, 100)\n",
+        "        self.fc2 = nn.Linear(100, 50)\n",
+        "        self.output = nn.Linear(50, N_out)\n",
+        "        self.sigmoid = nn.Sigmoid()\n",
+        "\n",
+        "\n",
+        "    def forward(self, x):\n",
+        "    \tx=self.input(x)\n",
+        "    \tx= self.fc1(x)\n",
+        "    \tx = self.sigmoid(x)\n",
+        "    \tx=self.fc2(x)\n",
+        "    \tx = self.Output(x)\n",
+        "    \treturn x"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SE7W9rpxI-iH",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "network = Network(800,25)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HsOAqG1dJC8N",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 136
+        },
+        "outputId": "901cf8b4-38f4-4570-ca32-bf3821460af4"
+      },
+      "source": [
+        "network"
+      ],
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Network(\n",
+              "  (input): Linear(in_features=800, out_features=400, bias=True)\n",
+              "  (fc1): Linear(in_features=400, out_features=100, bias=True)\n",
+              "  (fc2): Linear(in_features=100, out_features=50, bias=True)\n",
+              "  (output): Linear(in_features=50, out_features=25, bias=True)\n",
+              "  (sigmoid): Sigmoid()\n",
+              ")"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 4
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "sKGnDl15Jr75",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        ""
+      ],
+      "execution_count": 0,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file