understanding Pytorch implementing gradient descent and linear regression from scartch.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled",
      "version": "0.3.2",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "xJbDNspvSkrN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from torch import *\n",
        "import numpy as np\n",
        "import pandas"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Sz-7JHjHsqqk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        },
        "outputId": "715ca102-ad96-470e-94c0-255874c4be9e"
      },
      "source": [
        "!pip install torchviz"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: torchviz in /usr/local/lib/python3.6/dist-packages (0.0.1)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.6/dist-packages (from torchviz) (1.1.0)\n",
            "Requirement already satisfied: graphviz in /usr/local/lib/python3.6/dist-packages (from torchviz) (0.10.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from torch->torchviz) (1.16.4)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KGj39z59Srpl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "np.random.seed(42)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gbZvyCLUT5zK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x=np.random.randn(100,1)\n",
        "y = 1 + 2 * x + .1 * np.random.randn(100, 1)\n",
        "\n",
        "\n",
        "idx = np.arange(100)\n",
        "np.random.shuffle(idx)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n1fg0hFRgv3K",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "train_idx= idx[:80]\n",
        "test_idx=idx[80:]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7qNUHgldg98e",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x_train, y_train = x[train_idx], y[train_idx]\n",
        "x_test, y_test = x[test_idx], y[test_idx]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hGa3SLI9hGbJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "np.random.seed(52)\n",
        "a=np.random.randn(1)\n",
        "b=np.random.randn(1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C4yXXbhJhe1L",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "7dec585e-46cb-4f50-850a-a3870930c6e4"
      },
      "source": [
        "print(a, b)\n",
        "lr = 1e-1\n",
        "n_epochs = 10000\n"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.51947584] [-1.26875038]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7_VwId8mhlk-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "for epoch in range(n_epochs):\n",
        "  yhat=a+b*x_train\n",
        "  error=(y_train-yhat)\n",
        "  loss=(error**2).mean()\n",
        "  \n",
        "  a_grad=-2*error.mean()\n",
        "  b_grad=-2*(x_train*error).mean()\n",
        "  \n",
        "  a=a-lr*a_grad\n",
        "  b=b-lr*b_grad\n",
        "    \n",
        "  "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VHuesfgujd21",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "6ac90c77-2f6f-49f3-cf1e-73d4e02d7e4a"
      },
      "source": [
        "print(a,b)"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.99578039] [1.98516866]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "73BrEUf5jG-U",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4264c966-0e03-4105-b8a4-33acb95efb68"
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "linr = LinearRegression()\n",
        "linr.fit(x_train, y_train)\n",
        "print(linr.intercept_, linr.coef_[0])"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.99578039] [1.98516866]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XuRjsDFbjOKJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "9cca29a9-ba0f-4f75-edef-717ce40e1154"
      },
      "source": [
        "import torch\n",
        "import torch.optim as optim\n",
        "import torch.nn as nn\n",
        "from torchviz import make_dot\n",
        "\n",
        "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
        "\n",
        "\n",
        "x_train_tensor = torch.from_numpy(x_train).float().to(device)\n",
        "y_train_tensor = torch.from_numpy(y_train).float().to(device)\n",
        "\n",
        "\n",
        "print(type(x_train), type(x_train_tensor), x_train_tensor.type())"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'numpy.ndarray'> <class 'torch.Tensor'> torch.FloatTensor\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j_G241TdskUU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "a_t=torch.randn(1,requires_grad=True,dtype=torch.float)\n",
        "b_t=torch.randn(1,requires_grad=True,dtype=torch.float)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3d7OsqlwtiXL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "7312e592-f477-417b-8f29-9951380287ed"
      },
      "source": [
        "print(a_t,b_t)"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([0.9216], requires_grad=True) tensor([1.5691], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rScXRmxMuCAl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "86515541-e08a-4952-8e46-7d0429b818bb"
      },
      "source": [
        "# SECOND\n",
        "# But what if we want to run it on a GPU? We could just send them to device, right?\n",
        "a_t = torch.randn(1, requires_grad=True, dtype=torch.float).to(device)\n",
        "b_t = torch.randn(1, requires_grad=True, dtype=torch.float).to(device)\n",
        "print(a, b)\n",
        "# Sorry, but NO! The to(device) \"shadows\" the gradient...\n",
        "\n",
        "# THIRD\n",
        " #We can either create regular tensors and send them to the device (as we did with our data)\n",
        "a = torch.randn(1, dtype=torch.float).to(device)\n",
        "b = torch.randn(1, dtype=torch.float).to(device)\n",
        "# and THEN set them as requiring gradients...\n",
        "a.requires_grad_()\n",
        "b.requires_grad_()\n",
        "print(a, b)"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([1.1565], requires_grad=True) tensor([-0.0562], requires_grad=True)\n",
            "tensor([-0.5876], requires_grad=True) tensor([-0.1655], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ejV0Y0K6u5bq",
        "colab_type": "text"
      },
      "source": [
        "Always remmeber in pytorch if any method ends with a underscore then when it is applied to any variable it makes changes  to that variable inplace.That is why there is a significant diffrence between required_grad() and required_grad_(). "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y3BRo1Lrudn7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "80614d91-a39c-422f-dddb-9ad308071ec2"
      },
      "source": [
        "#another easier approach to declare your variables and at the time of there declaration send them directly to the device like this\n",
        "torch.manual_seed(42)\n",
        "a_t = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "b_t = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "print(a, b)"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([-0.5876], requires_grad=True) tensor([-0.1655], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LsPdifu3wHAT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7e10eb4a-79f9-41c6-87ce-54109d083237"
      },
      "source": [
        "lr = 1e-1\n",
        "n_epochs = 1000\n",
        "\n",
        "torch.manual_seed(42)\n",
        "a = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "b = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "\n",
        "for epoch in range(n_epochs):\n",
        "    yhat = a + b * x_train_tensor\n",
        "    error = y_train_tensor - yhat\n",
        "    loss = (error ** 2).mean()\n",
        "\n",
        "    # No more manual computation of gradients! \n",
        "    # a_grad = -2 * error.mean()\n",
        "    # b_grad = -2 * (x_tensor * error).mean()\n",
        "    \n",
        "    # We just tell PyTorch to work its way BACKWARDS from the specified loss!\n",
        "    loss.backward()\n",
        "    # Let's check the computed gradients...\n",
        "    print(a.grad)\n",
        "    print(b.grad)\n",
        "    \n",
        "    # What about UPDATING the parameters? Not so fast...\n",
        "    \n",
        "    # FIRST ATTEMPT\n",
        "    # AttributeError: 'NoneType' object has no attribute 'zero_'\n",
        "    # a = a - lr * a.grad\n",
        "    # b = b - lr * b.grad\n",
        "    # print(a)\n",
        "\n",
        "    # SECOND ATTEMPT\n",
        "    # RuntimeError: a leaf Variable that requires grad has been used in an in-place operation.\n",
        "    # a -= lr * a.grad\n",
        "    # b -= lr * b.grad        \n",
        "    \n",
        "    # THIRD ATTEMPT\n",
        "    # We need to use NO_GRAD to keep the update out of the gradient computation\n",
        "    # Why is that? It boils down to the DYNAMIC GRAPH that PyTorch uses...\n",
        "    with torch.no_grad():\n",
        "        a -= lr * a.grad\n",
        "        b -= lr * b.grad\n",
        "    \n",
        "    # PyTorch is \"clingy\" to its computed gradients, we need to tell it to let it go...\n",
        "    a.grad.zero_()\n",
        "    b.grad.zero_()\n",
        "    \n",
        "print(a, b)\n"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([-1.1663])\n",
            "tensor([-2.8676])\n",
            "tensor([-0.9565])\n",
            "tensor([-2.4258])\n",
            "tensor([-0.7850])\n",
            "tensor([-2.0519])\n",
            "tensor([-0.6448])\n",
            "tensor([-1.7354])\n",
            "tensor([-0.5301])\n",
            "tensor([-1.4675])\n",
            "tensor([-0.4361])\n",
            "tensor([-1.2409])\n",
            "tensor([-0.3590])\n",
            "tensor([-1.0492])\n",
            "tensor([-0.2958])\n",
            "tensor([-0.8870])\n",
            "tensor([-0.2439])\n",
            "tensor([-0.7498])\n",
            "tensor([-0.2012])\n",
            "tensor([-0.6338])\n",
            "tensor([-0.1662])\n",
            "tensor([-0.5357])\n",
            "tensor([-0.1373])\n",
            "tensor([-0.4528])\n",
            "tensor([-0.1136])\n",
            "tensor([-0.3826])\n",
            "tensor([-0.0940])\n",
            "tensor([-0.3234])\n",
            "tensor([-0.0778])\n",
            "tensor([-0.2732])\n",
            "tensor([-0.0645])\n",
            "tensor([-0.2309])\n",
            "tensor([-0.0535])\n",
            "tensor([-0.1951])\n",
            "tensor([-0.0444])\n",
            "tensor([-0.1648])\n",
            "tensor([-0.0369])\n",
            "tensor([-0.1392])\n",
            "tensor([-0.0306])\n",
            "tensor([-0.1176])\n",
            "tensor([-0.0255])\n",
            "tensor([-0.0994])\n",
            "tensor([-0.0212])\n",
            "tensor([-0.0839])\n",
            "tensor([-0.0176])\n",
            "tensor([-0.0709])\n",
            "tensor([-0.0147])\n",
            "tensor([-0.0599])\n",
            "tensor([-0.0122])\n",
            "tensor([-0.0506])\n",
            "tensor([-0.0102])\n",
            "tensor([-0.0427])\n",
            "tensor([-0.0085])\n",
            "tensor([-0.0361])\n",
            "tensor([-0.0071])\n",
            "tensor([-0.0305])\n",
            "tensor([-0.0059])\n",
            "tensor([-0.0257])\n",
            "tensor([-0.0050])\n",
            "tensor([-0.0217])\n",
            "tensor([-0.0041])\n",
            "tensor([-0.0184])\n",
            "tensor([-0.0035])\n",
            "tensor([-0.0155])\n",
            "tensor([-0.0029])\n",
            "tensor([-0.0131])\n",
            "tensor([-0.0024])\n",
            "tensor([-0.0111])\n",
            "tensor([-0.0020])\n",
            "tensor([-0.0093])\n",
            "tensor([-0.0017])\n",
            "tensor([-0.0079])\n",
            "tensor([-0.0014])\n",
            "tensor([-0.0067])\n",
            "tensor([-0.0012])\n",
            "tensor([-0.0056])\n",
            "tensor([-0.0010])\n",
            "tensor([-0.0047])\n",
            "tensor([-0.0008])\n",
            "tensor([-0.0040])\n",
            "tensor([-0.0007])\n",
            "tensor([-0.0034])\n",
            "tensor([-0.0006])\n",
            "tensor([-0.0029])\n",
            "tensor([-0.0005])\n",
            "tensor([-0.0024])\n",
            "tensor([-0.0004])\n",
            "tensor([-0.0020])\n",
            "tensor([-0.0004])\n",
            "tensor([-0.0017])\n",
            "tensor([-0.0003])\n",
            "tensor([-0.0015])\n",
            "tensor([-0.0002])\n",
            "tensor([-0.0012])\n",
            "tensor([-0.0002])\n",
            "tensor([-0.0010])\n",
            "tensor([-0.0002])\n",
            "tensor([-0.0009])\n",
            "tensor([-0.0001])\n",
            "tensor([-0.0007])\n",
            "tensor([-0.0001])\n",
            "tensor([-0.0006])\n",
            "tensor([-0.0001])\n",
            "tensor([-0.0005])\n",
            "tensor([-8.7502e-05])\n",
            "tensor([-0.0004])\n",
            "tensor([-7.3598e-05])\n",
            "tensor([-0.0004])\n",
            "tensor([-6.1983e-05])\n",
            "tensor([-0.0003])\n",
            "tensor([-5.2175e-05])\n",
            "tensor([-0.0003])\n",
            "tensor([-4.3892e-05])\n",
            "tensor([-0.0002])\n",
            "tensor([-3.6908e-05])\n",
            "tensor([-0.0002])\n",
            "tensor([-3.1077e-05])\n",
            "tensor([-0.0002])\n",
            "tensor([-2.6184e-05])\n",
            "tensor([-0.0001])\n",
            "tensor([-2.2033e-05])\n",
            "tensor([-0.0001])\n",
            "tensor([-1.8603e-05])\n",
            "tensor([-9.6560e-05])\n",
            "tensor([-1.5657e-05])\n",
            "tensor([-8.1542e-05])\n",
            "tensor([-1.3282e-05])\n",
            "tensor([-6.8849e-05])\n",
            "tensor([-1.1179e-05])\n",
            "tensor([-5.8150e-05])\n",
            "tensor([-9.3852e-06])\n",
            "tensor([-4.8984e-05])\n",
            "tensor([-7.8916e-06])\n",
            "tensor([-4.1348e-05])\n",
            "tensor([-6.6741e-06])\n",
            "tensor([-3.4892e-05])\n",
            "tensor([-5.6510e-06])\n",
            "tensor([-2.9486e-05])\n",
            "tensor([-4.7986e-06])\n",
            "tensor([-2.4858e-05])\n",
            "tensor([-4.0522e-06])\n",
            "tensor([-2.0949e-05])\n",
            "tensor([-3.4410e-06])\n",
            "tensor([-1.7567e-05])\n",
            "tensor([-2.8396e-06])\n",
            "tensor([-1.4821e-05])\n",
            "tensor([-2.3895e-06])\n",
            "tensor([-1.2615e-05])\n",
            "tensor([-1.9919e-06])\n",
            "tensor([-1.0514e-05])\n",
            "tensor([-1.7683e-06])\n",
            "tensor([-8.8755e-06])\n",
            "tensor([-1.4354e-06])\n",
            "tensor([-7.5819e-06])\n",
            "tensor([-1.2747e-06])\n",
            "tensor([-6.4042e-06])\n",
            "tensor([-1.0703e-06])\n",
            "tensor([-5.5649e-06])\n",
            "tensor([-8.6613e-07])\n",
            "tensor([-4.5949e-06])\n",
            "tensor([-7.8650e-07])\n",
            "tensor([-3.8981e-06])\n",
            "tensor([-6.9104e-07])\n",
            "tensor([-3.3360e-06])\n",
            "tensor([-6.1956e-07])\n",
            "tensor([-2.7716e-06])\n",
            "tensor([-5.4901e-07])\n",
            "tensor([-2.3509e-06])\n",
            "tensor([-4.0932e-07])\n",
            "tensor([-1.9392e-06])\n",
            "tensor([-3.0943e-07])\n",
            "tensor([-1.6484e-06])\n",
            "tensor([-2.2771e-07])\n",
            "tensor([-1.4659e-06])\n",
            "tensor([-2.1746e-07])\n",
            "tensor([-1.2994e-06])\n",
            "tensor([-2.3842e-07])\n",
            "tensor([-1.0284e-06])\n",
            "tensor([-2.1653e-07])\n",
            "tensor([-8.6543e-07])\n",
            "tensor([-2.3050e-07])\n",
            "tensor([-7.0594e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([-2.7334e-07])\n",
            "tensor([-5.1362e-07])\n",
            "tensor([0.9958], requires_grad=True) tensor([1.9852], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kcqeQ-VC7Srw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "torch.manual_seed(42)\n",
        "a = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "b = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "\n",
        "yhat = a + b * x_train_tensor\n",
        "error = y_train_tensor - yhat\n",
        "loss = (error ** 2).mean()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "euVm3-Rq8CCu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 249
        },
        "outputId": "11bc67f9-3a54-42dd-c2dc-e1369f938b53"
      },
      "source": [
        "make_dot(yhat)"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.dot.Digraph at 0x7fbc7a9f1c18>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: %3 Pages: 1 -->\n<svg width=\"172pt\" height=\"171pt\"\n viewBox=\"0.00 0.00 171.50 171.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 167)\">\n<title>%3</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-167 167.5,-167 167.5,4 -4,4\"/>\n<!-- 140447487826408 -->\n<g id=\"node1\" class=\"node\">\n<title>140447487826408</title>\n<polygon fill=\"#caff70\" stroke=\"#000000\" points=\"118,-21 26,-21 26,0 118,0 118,-21\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-7.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">AddBackward0</text>\n</g>\n<!-- 140447487825960 -->\n<g id=\"node2\" class=\"node\">\n<title>140447487825960</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"54,-92 0,-92 0,-57 54,-57 54,-92\"/>\n<text text-anchor=\"middle\" x=\"27\" y=\"-64.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487825960&#45;&gt;140447487826408 -->\n<g id=\"edge1\" class=\"edge\">\n<title>140447487825960&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M39.535,-56.6724C45.4798,-48.2176 52.5878,-38.1085 58.6352,-29.5078\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"61.5714,-31.4169 64.4601,-21.2234 55.8452,-27.3906 61.5714,-31.4169\"/>\n</g>\n<!-- 140447487826072 -->\n<g id=\"node3\" class=\"node\">\n<title>140447487826072</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"163.5,-85 72.5,-85 72.5,-64 163.5,-64 163.5,-85\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-71.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MulBackward0</text>\n</g>\n<!-- 140447487826072&#45;&gt;140447487826408 -->\n<g id=\"edge2\" class=\"edge\">\n<title>140447487826072&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M110.404,-63.9317C103.7191,-54.6309 93.821,-40.8597 85.7479,-29.6276\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"88.4395,-27.3753 79.761,-21.2979 82.7553,-31.4608 88.4395,-27.3753\"/>\n</g>\n<!-- 140447487826632 -->\n<g id=\"node4\" class=\"node\">\n<title>140447487826632</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"145,-163 91,-163 91,-128 145,-128 145,-163\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-135.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487826632&#45;&gt;140447487826072 -->\n<g id=\"edge3\" class=\"edge\">\n<title>140447487826632&#45;&gt;140447487826072</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M118,-127.9494C118,-118.058 118,-105.6435 118,-95.2693\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"121.5001,-95.0288 118,-85.0288 114.5001,-95.0289 121.5001,-95.0288\"/>\n</g>\n</g>\n</svg>\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "urQ0xtNv8Jhs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "outputId": "d47f346f-3e36-478a-dcb7-cc6b8092818b"
      },
      "source": [
        "make_dot(error)"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.dot.Digraph at 0x7fbc7a9f1710>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: %3 Pages: 1 -->\n<svg width=\"172pt\" height=\"228pt\"\n viewBox=\"0.00 0.00 171.50 228.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 224)\">\n<title>%3</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-224 167.5,-224 167.5,4 -4,4\"/>\n<!-- 140447487826184 -->\n<g id=\"node1\" class=\"node\">\n<title>140447487826184</title>\n<polygon fill=\"#caff70\" stroke=\"#000000\" points=\"117,-21 27,-21 27,0 117,0 117,-21\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-7.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">SubBackward0</text>\n</g>\n<!-- 140447487826408 -->\n<g id=\"node2\" class=\"node\">\n<title>140447487826408</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"118,-78 26,-78 26,-57 118,-57 118,-78\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-64.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">AddBackward0</text>\n</g>\n<!-- 140447487826408&#45;&gt;140447487826184 -->\n<g id=\"edge1\" class=\"edge\">\n<title>140447487826408&#45;&gt;140447487826184</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M72,-56.7787C72,-49.6134 72,-39.9517 72,-31.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"75.5001,-31.1732 72,-21.1732 68.5001,-31.1732 75.5001,-31.1732\"/>\n</g>\n<!-- 140447487825960 -->\n<g id=\"node3\" class=\"node\">\n<title>140447487825960</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"54,-149 0,-149 0,-114 54,-114 54,-149\"/>\n<text text-anchor=\"middle\" x=\"27\" y=\"-121.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487825960&#45;&gt;140447487826408 -->\n<g id=\"edge2\" class=\"edge\">\n<title>140447487825960&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M39.535,-113.6724C45.4798,-105.2176 52.5878,-95.1085 58.6352,-86.5078\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"61.5714,-88.4169 64.4601,-78.2234 55.8452,-84.3906 61.5714,-88.4169\"/>\n</g>\n<!-- 140447487826072 -->\n<g id=\"node4\" class=\"node\">\n<title>140447487826072</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"163.5,-142 72.5,-142 72.5,-121 163.5,-121 163.5,-142\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-128.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MulBackward0</text>\n</g>\n<!-- 140447487826072&#45;&gt;140447487826408 -->\n<g id=\"edge3\" class=\"edge\">\n<title>140447487826072&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M110.404,-120.9317C103.7191,-111.6309 93.821,-97.8597 85.7479,-86.6276\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"88.4395,-84.3753 79.761,-78.2979 82.7553,-88.4608 88.4395,-84.3753\"/>\n</g>\n<!-- 140447487826632 -->\n<g id=\"node5\" class=\"node\">\n<title>140447487826632</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"145,-220 91,-220 91,-185 145,-185 145,-220\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-192.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487826632&#45;&gt;140447487826072 -->\n<g id=\"edge4\" class=\"edge\">\n<title>140447487826632&#45;&gt;140447487826072</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M118,-184.9494C118,-175.058 118,-162.6435 118,-152.2693\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"121.5001,-152.0288 118,-142.0288 114.5001,-152.0289 121.5001,-152.0288\"/>\n</g>\n</g>\n</svg>\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9cGa1URM8S7Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 477
        },
        "outputId": "6e0f8ad1-c59b-479d-f4b5-2fd7175da8d6"
      },
      "source": [
        "make_dot(loss)"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.dot.Digraph at 0x7fbc7a9f1fd0>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: %3 Pages: 1 -->\n<svg width=\"172pt\" height=\"342pt\"\n viewBox=\"0.00 0.00 171.50 342.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 338)\">\n<title>%3</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-338 167.5,-338 167.5,4 -4,4\"/>\n<!-- 140447487826296 -->\n<g id=\"node1\" class=\"node\">\n<title>140447487826296</title>\n<polygon fill=\"#caff70\" stroke=\"#000000\" points=\"121,-21 23,-21 23,0 121,0 121,-21\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-7.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MeanBackward0</text>\n</g>\n<!-- 140447487825568 -->\n<g id=\"node2\" class=\"node\">\n<title>140447487825568</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"118.5,-78 25.5,-78 25.5,-57 118.5,-57 118.5,-78\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-64.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">PowBackward0</text>\n</g>\n<!-- 140447487825568&#45;&gt;140447487826296 -->\n<g id=\"edge1\" class=\"edge\">\n<title>140447487825568&#45;&gt;140447487826296</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M72,-56.7787C72,-49.6134 72,-39.9517 72,-31.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"75.5001,-31.1732 72,-21.1732 68.5001,-31.1732 75.5001,-31.1732\"/>\n</g>\n<!-- 140447487826184 -->\n<g id=\"node3\" class=\"node\">\n<title>140447487826184</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"117,-135 27,-135 27,-114 117,-114 117,-135\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-121.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">SubBackward0</text>\n</g>\n<!-- 140447487826184&#45;&gt;140447487825568 -->\n<g id=\"edge2\" class=\"edge\">\n<title>140447487826184&#45;&gt;140447487825568</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M72,-113.7787C72,-106.6134 72,-96.9517 72,-88.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"75.5001,-88.1732 72,-78.1732 68.5001,-88.1732 75.5001,-88.1732\"/>\n</g>\n<!-- 140447487826408 -->\n<g id=\"node4\" class=\"node\">\n<title>140447487826408</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"118,-192 26,-192 26,-171 118,-171 118,-192\"/>\n<text text-anchor=\"middle\" x=\"72\" y=\"-178.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">AddBackward0</text>\n</g>\n<!-- 140447487826408&#45;&gt;140447487826184 -->\n<g id=\"edge3\" class=\"edge\">\n<title>140447487826408&#45;&gt;140447487826184</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M72,-170.7787C72,-163.6134 72,-153.9517 72,-145.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"75.5001,-145.1732 72,-135.1732 68.5001,-145.1732 75.5001,-145.1732\"/>\n</g>\n<!-- 140447487825960 -->\n<g id=\"node5\" class=\"node\">\n<title>140447487825960</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"54,-263 0,-263 0,-228 54,-228 54,-263\"/>\n<text text-anchor=\"middle\" x=\"27\" y=\"-235.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487825960&#45;&gt;140447487826408 -->\n<g id=\"edge4\" class=\"edge\">\n<title>140447487825960&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M39.535,-227.6724C45.4798,-219.2176 52.5878,-209.1085 58.6352,-200.5078\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"61.5714,-202.4169 64.4601,-192.2234 55.8452,-198.3906 61.5714,-202.4169\"/>\n</g>\n<!-- 140447487826072 -->\n<g id=\"node6\" class=\"node\">\n<title>140447487826072</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"163.5,-256 72.5,-256 72.5,-235 163.5,-235 163.5,-256\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-242.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MulBackward0</text>\n</g>\n<!-- 140447487826072&#45;&gt;140447487826408 -->\n<g id=\"edge5\" class=\"edge\">\n<title>140447487826072&#45;&gt;140447487826408</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M110.404,-234.9317C103.7191,-225.6309 93.821,-211.8597 85.7479,-200.6276\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"88.4395,-198.3753 79.761,-192.2979 82.7553,-202.4608 88.4395,-198.3753\"/>\n</g>\n<!-- 140447487826632 -->\n<g id=\"node7\" class=\"node\">\n<title>140447487826632</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"145,-334 91,-334 91,-299 145,-299 145,-334\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-306.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487826632&#45;&gt;140447487826072 -->\n<g id=\"edge6\" class=\"edge\">\n<title>140447487826632&#45;&gt;140447487826072</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M118,-298.9494C118,-289.058 118,-276.6435 118,-266.2693\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"121.5001,-266.0288 118,-256.0288 114.5001,-266.0289 121.5001,-266.0288\"/>\n</g>\n</g>\n</svg>\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tQf90Q-d8d9n",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#iknow this computation doesn't make nay sense but this is to demosntrate you can dynamic computation graphs in pytorch even using control flow statements\n",
        "\n",
        "yhat=a+b*x_train_tensor\n",
        "error=y_train_tensor-yhat\n",
        "loss=(error**2).mean()\n",
        "\n",
        "if loss>0:\n",
        "  yhat2=b*x_train_tensor\n",
        "  error2=y_train_tensor-yhat2\n",
        "  \n",
        "  \n",
        "loss+=error2.mean()  "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lFZtGYU29uYI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 553
        },
        "outputId": "61aed3f2-0257-4ef7-ebda-53b6b2d6d588"
      },
      "source": [
        "make_dot(loss)"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.dot.Digraph at 0x7fbc7aa01470>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: %3 Pages: 1 -->\n<svg width=\"284pt\" height=\"399pt\"\n viewBox=\"0.00 0.00 284.00 399.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 395)\">\n<title>%3</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-395 280,-395 280,4 -4,4\"/>\n<!-- 140447487890600 -->\n<g id=\"node1\" class=\"node\">\n<title>140447487890600</title>\n<polygon fill=\"#caff70\" stroke=\"#000000\" points=\"215,-21 123,-21 123,0 215,0 215,-21\"/>\n<text text-anchor=\"middle\" x=\"169\" y=\"-7.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">AddBackward0</text>\n</g>\n<!-- 140447487827752 -->\n<g id=\"node2\" class=\"node\">\n<title>140447487827752</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"180,-78 82,-78 82,-57 180,-57 180,-78\"/>\n<text text-anchor=\"middle\" x=\"131\" y=\"-64.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MeanBackward0</text>\n</g>\n<!-- 140447487827752&#45;&gt;140447487890600 -->\n<g id=\"edge1\" class=\"edge\">\n<title>140447487827752&#45;&gt;140447487890600</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M138.1475,-56.7787C143.2429,-49.1357 150.2317,-38.6524 156.2694,-29.596\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"159.2497,-31.4352 161.8845,-21.1732 153.4253,-27.5522 159.2497,-31.4352\"/>\n</g>\n<!-- 140447487827584 -->\n<g id=\"node3\" class=\"node\">\n<title>140447487827584</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"159.5,-135 66.5,-135 66.5,-114 159.5,-114 159.5,-135\"/>\n<text text-anchor=\"middle\" x=\"113\" y=\"-121.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">PowBackward0</text>\n</g>\n<!-- 140447487827584&#45;&gt;140447487827752 -->\n<g id=\"edge2\" class=\"edge\">\n<title>140447487827584&#45;&gt;140447487827752</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M116.3857,-113.7787C118.6987,-106.4542 121.8354,-96.5211 124.61,-87.7352\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"127.9557,-88.763 127.6295,-78.1732 121.2806,-86.655 127.9557,-88.763\"/>\n</g>\n<!-- 140447487825288 -->\n<g id=\"node4\" class=\"node\">\n<title>140447487825288</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"158,-192 68,-192 68,-171 158,-171 158,-192\"/>\n<text text-anchor=\"middle\" x=\"113\" y=\"-178.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">SubBackward0</text>\n</g>\n<!-- 140447487825288&#45;&gt;140447487827584 -->\n<g id=\"edge3\" class=\"edge\">\n<title>140447487825288&#45;&gt;140447487827584</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M113,-170.7787C113,-163.6134 113,-153.9517 113,-145.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"116.5001,-145.1732 113,-135.1732 109.5001,-145.1732 116.5001,-145.1732\"/>\n</g>\n<!-- 140447487826856 -->\n<g id=\"node5\" class=\"node\">\n<title>140447487826856</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"159,-249 67,-249 67,-228 159,-228 159,-249\"/>\n<text text-anchor=\"middle\" x=\"113\" y=\"-235.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">AddBackward0</text>\n</g>\n<!-- 140447487826856&#45;&gt;140447487825288 -->\n<g id=\"edge4\" class=\"edge\">\n<title>140447487826856&#45;&gt;140447487825288</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M113,-227.7787C113,-220.6134 113,-210.9517 113,-202.3097\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"116.5001,-202.1732 113,-192.1732 109.5001,-202.1732 116.5001,-202.1732\"/>\n</g>\n<!-- 140447487826520 -->\n<g id=\"node6\" class=\"node\">\n<title>140447487826520</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"54,-320 0,-320 0,-285 54,-285 54,-320\"/>\n<text text-anchor=\"middle\" x=\"27\" y=\"-292.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487826520&#45;&gt;140447487826856 -->\n<g id=\"edge5\" class=\"edge\">\n<title>140447487826520&#45;&gt;140447487826856</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M50.9558,-284.6724C63.3538,-275.446 78.3987,-264.2498 90.5683,-255.1934\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"92.9097,-257.8138 98.8425,-249.0358 88.7306,-252.1981 92.9097,-257.8138\"/>\n</g>\n<!-- 140447487823944 -->\n<g id=\"node7\" class=\"node\">\n<title>140447487823944</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"163.5,-313 72.5,-313 72.5,-292 163.5,-292 163.5,-313\"/>\n<text text-anchor=\"middle\" x=\"118\" y=\"-299.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MulBackward0</text>\n</g>\n<!-- 140447487823944&#45;&gt;140447487826856 -->\n<g id=\"edge6\" class=\"edge\">\n<title>140447487823944&#45;&gt;140447487826856</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M117.1744,-291.9317C116.4837,-283.0913 115.4775,-270.2122 114.6261,-259.3135\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"118.1119,-258.9949 113.8436,-249.2979 111.1332,-259.5402 118.1119,-258.9949\"/>\n</g>\n<!-- 140447487824224 -->\n<g id=\"node8\" class=\"node\">\n<title>140447487824224</title>\n<polygon fill=\"#add8e6\" stroke=\"#000000\" points=\"199,-391 145,-391 145,-356 199,-356 199,-391\"/>\n<text text-anchor=\"middle\" x=\"172\" y=\"-363.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\"> (1)</text>\n</g>\n<!-- 140447487824224&#45;&gt;140447487823944 -->\n<g id=\"edge7\" class=\"edge\">\n<title>140447487824224&#45;&gt;140447487823944</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M158.6517,-355.9494C150.6484,-345.4266 140.4734,-332.0484 132.3053,-321.3089\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"134.8474,-318.8695 126.0078,-313.0288 129.2757,-323.1071 134.8474,-318.8695\"/>\n</g>\n<!-- 140447487827304 -->\n<g id=\"node11\" class=\"node\">\n<title>140447487827304</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"272.5,-313 181.5,-313 181.5,-292 272.5,-292 272.5,-313\"/>\n<text text-anchor=\"middle\" x=\"227\" y=\"-299.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MulBackward0</text>\n</g>\n<!-- 140447487824224&#45;&gt;140447487827304 -->\n<g id=\"edge11\" class=\"edge\">\n<title>140447487824224&#45;&gt;140447487827304</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M185.5955,-355.9494C193.8285,-345.3214 204.3179,-331.7806 212.6787,-320.9875\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"215.4868,-323.0778 218.8439,-313.0288 209.9529,-318.7909 215.4868,-323.0778\"/>\n</g>\n<!-- 140447487825624 -->\n<g id=\"node9\" class=\"node\">\n<title>140447487825624</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"276,-135 178,-135 178,-114 276,-114 276,-135\"/>\n<text text-anchor=\"middle\" x=\"227\" y=\"-121.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">MeanBackward0</text>\n</g>\n<!-- 140447487825624&#45;&gt;140447487890600 -->\n<g id=\"edge8\" class=\"edge\">\n<title>140447487825624&#45;&gt;140447487890600</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M221.6475,-113.9795C211.9855,-94.9888 191.4875,-54.6995 179.1119,-30.3751\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"182.1629,-28.6533 174.5088,-21.3276 175.9239,-31.8275 182.1629,-28.6533\"/>\n</g>\n<!-- 140447487827808 -->\n<g id=\"node10\" class=\"node\">\n<title>140447487827808</title>\n<polygon fill=\"#d3d3d3\" stroke=\"#000000\" points=\"272,-249 182,-249 182,-228 272,-228 272,-249\"/>\n<text text-anchor=\"middle\" x=\"227\" y=\"-235.4\" font-family=\"Times,serif\" font-size=\"12.00\" fill=\"#000000\">SubBackward0</text>\n</g>\n<!-- 140447487827808&#45;&gt;140447487825624 -->\n<g id=\"edge9\" class=\"edge\">\n<title>140447487827808&#45;&gt;140447487825624</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M227,-227.9795C227,-209.242 227,-169.7701 227,-145.3565\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"230.5001,-145.3276 227,-135.3276 223.5001,-145.3277 230.5001,-145.3276\"/>\n</g>\n<!-- 140447487827304&#45;&gt;140447487827808 -->\n<g id=\"edge10\" class=\"edge\">\n<title>140447487827304&#45;&gt;140447487827808</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M227,-291.9317C227,-283.0913 227,-270.2122 227,-259.3135\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"230.5001,-259.2979 227,-249.2979 223.5001,-259.2979 230.5001,-259.2979\"/>\n</g>\n</g>\n</svg>\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_1m-QTtD9wpt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "d38c7b39-e9f1-4b76-afb7-959bb9b29bf2"
      },
      "source": [
        "#now let us see how we can compute gradients when we have many paramaters we will use the optimizer method with step finction and zero_grad , you can any kind of optimizer present in the pytorch docs that can be sgd or adam\n",
        "torch.manual_seed(42)\n",
        "a = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "b = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "print(a, b)\n",
        "\n",
        "lr = 1e-1\n",
        "n_epochs = 1000\n",
        "\n",
        "# Defines a SGD optimizer to update the parameters\n",
        "optimizer = optim.SGD([a, b], lr=lr)\n",
        "\n",
        "for epoch in range(n_epochs):\n",
        "    yhat = a + b * x_train_tensor\n",
        "    error = y_train_tensor - yhat\n",
        "    loss = (error ** 2).mean()\n",
        "\n",
        "    loss.backward()    \n",
        "    \n",
        "    # No more manual update!\n",
        "    # with torch.no_grad():\n",
        "    #     a -= lr * a.grad\n",
        "    #     b -= lr * b.grad\n",
        "    optimizer.step()\n",
        "    \n",
        "    # No more telling PyTorch to let gradients go!\n",
        "    # a.grad.zero_()\n",
        "    # b.grad.zero_()\n",
        "    optimizer.zero_grad()\n",
        "    \n",
        "print(a, b)"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([0.3367], requires_grad=True) tensor([0.1288], requires_grad=True)\n",
            "tensor([0.9958], requires_grad=True) tensor([1.9852], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PPEQqstP_BKQ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "cd86a199-aad1-4264-a350-38468a0dc214"
      },
      "source": [
        "#now let us tackle the loss computation using the pytorch usefull nn module using the predefined loss functions\n",
        "torch.manual_seed(42)\n",
        "a = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "b = torch.randn(1, requires_grad=True, dtype=torch.float, device=device)\n",
        "print(a, b)\n",
        "\n",
        "lr = 1e-1\n",
        "n_epochs = 1000\n",
        "\n",
        "# Defines a MSE loss function\n",
        "loss_fn = nn.MSELoss(reduction='mean')\n",
        "\n",
        "optimizer = optim.SGD([a, b], lr=lr)\n",
        "\n",
        "for epoch in range(n_epochs):\n",
        "    yhat = a + b * x_train_tensor\n",
        "    \n",
        "    # No more manual loss!\n",
        "    # error = y_tensor - yhat\n",
        "    # loss = (error ** 2).mean()\n",
        "    loss = loss_fn(y_train_tensor, yhat)\n",
        "\n",
        "    loss.backward()    \n",
        "    optimizer.step()\n",
        "    optimizer.zero_grad()\n",
        "    \n",
        "print(a, b)\n"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([0.3367], requires_grad=True) tensor([0.1288], requires_grad=True)\n",
            "tensor([0.9958], requires_grad=True) tensor([1.9852], requires_grad=True)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JfZ2KmbJA6EI",
        "colab_type": "text"
      },
      "source": [
        "So!!! as you can see it works really well i am actually falling in love with pytorch\n",
        "Now let us automate the whole process using the beautiful functions of pytorch"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IsmW-8UMA2pV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class MLR(nn.Module):\n",
        "  def _init_(self):\n",
        "    super._init_()\n",
        "     # To make \"a\" and \"b\" real parameters of the model, we need to wrap them with nn.Parameter\n",
        "    self.a = nn.ModuleList(Parameter(torch.randn(1, requires_grad=True, dtype=torch.float)))\n",
        "    self.b = nn.ModuleList(Parameter(torch.randn(1, requires_grad=True, dtype=torch.float)))\n",
        "        \n",
        "  def forward(self,x):\n",
        "    \n",
        "    return self.a + self.b*x\n",
        "        \n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vFKZsOXwDCVq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "b4379652-c0ef-46b7-c39d-9ef2424299ec"
      },
      "source": [
        "torch.manual_seed(42)\n",
        "\n",
        "# Now we can create a model and send it at once to the device\n",
        "model = MLR().to(device)\n",
        "# We can also inspect its parameters using its state_dict\n",
        "print(model.state_dict())"
      ],
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "OrderedDict()\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "isD6gkWCDTUY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "00ede513-0f10-49a7-de17-b5ab4194f0d4"
      },
      "source": [
        "torch.manual_seed(42)\n",
        "\n",
        "# Now we can create a model and send it at once to the device\n",
        "model = MLR()\n",
        "# We can also inspect its parameters using its state_dict\n",
        "print(model.state_dict())\n",
        "\n",
        "\n",
        "#now let us fit our model\n",
        "lr=1e-1\n",
        "n_epochs=2000\n",
        "#loss finction using nn\n",
        "loss_fn=nn.MSELoss(reduction='mean')\n",
        "model=MLR()\n",
        "optimizer=optim.SGD(model.parameters(),lr=lr)\n",
        "for epoch in range(n_epochs):\n",
        "  #start model training\n",
        "  \n",
        "  model.train()\n",
        "  \n",
        "  #predictions of your model\n",
        "  yhat=model(x_train_tensor)\n",
        "  \n",
        "  loss=loss_fn(y_train_tensor,yhat)\n",
        "  loss.backward()\n",
        "  optimizer.step()\n",
        "  optimizer.zero_grad()\n",
        "  \n",
        "print(model.state_dict())  "
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "OrderedDict()\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-94-5f406079aa93>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0mloss_fn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMSELoss\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreduction\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mean'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mMLR\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0moptimizer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moptim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSGD\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_epochs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m   \u001b[0;31m#start model training\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/optim/sgd.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, params, lr, momentum, dampening, weight_decay, nesterov)\u001b[0m\n\u001b[1;32m     62\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnesterov\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmomentum\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mdampening\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Nesterov momentum requires a momentum and zero dampening\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m         \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSGD\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     65\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setstate__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/optim/optimizer.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, params, defaults)\u001b[0m\n\u001b[1;32m     43\u001b[0m         \u001b[0mparam_groups\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparam_groups\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"optimizer got an empty parameter list\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     46\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparam_groups\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m             \u001b[0mparam_groups\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'params'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mparam_groups\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: optimizer got an empty parameter list"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D7kc9SMzFD8M",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 370
        },
        "outputId": "78de1e35-69bc-402e-f26b-df77c4d3c371"
      },
      "source": [
        "\n",
        "def make_train_step(model, loss_fn, optimizer):\n",
        "    # Builds function that performs a step in the train loop\n",
        "    def train_step(x, y):\n",
        "        # Sets model to TRAIN mode\n",
        "        model.train()\n",
        "        # Makes predictions\n",
        "        yhat = model(x)\n",
        "        # Computes loss\n",
        "        loss = loss_fn(y, yhat)\n",
        "        # Computes gradients\n",
        "        loss.backward()\n",
        "        # Updates parameters and zeroes gradients\n",
        "        optimizer.step()\n",
        "        optimizer.zero_grad()\n",
        "        # Returns the loss\n",
        "        return loss.item()\n",
        "    \n",
        "    # Returns the function that will be called inside the train loop\n",
        "    return train_step\n",
        "\n",
        "# Creates the train_step function for our model, loss function and optimizer\n",
        "model=MLR()\n",
        "train_step = make_train_step(model, loss_fn, optimizer)\n",
        "losses = []\n",
        "\n",
        "# For each epoch...\n",
        "for epoch in range(n_epochs):\n",
        "    # Performs one train step and returns the corresponding loss\n",
        "    loss = train_step(x_train_tensor, y_train_tensor)\n",
        "    losses.append(loss)\n",
        "    \n",
        "# Checks model's parameters\n",
        "print(model.state_dict())"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-95-1ea09a0efdd0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_epochs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     \u001b[0;31m# Performs one train step and returns the corresponding loss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m     \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_train_tensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_train_tensor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m     \u001b[0mlosses\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-95-1ea09a0efdd0>\u001b[0m in \u001b[0;36mtrain_step\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m      6\u001b[0m         \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m         \u001b[0;31m# Makes predictions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m         \u001b[0myhat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      9\u001b[0m         \u001b[0;31m# Computes loss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m         \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloss_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myhat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m    491\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_slow_forward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    492\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 493\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    494\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhook\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_forward_hooks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    495\u001b[0m             \u001b[0mhook_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhook\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-92-448dd7f8e7c4>\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m      8\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0ma\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m    537\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mmodules\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    538\u001b[0m         raise AttributeError(\"'{}' object has no attribute '{}'\".format(\n\u001b[0;32m--> 539\u001b[0;31m             type(self).__name__, name))\n\u001b[0m\u001b[1;32m    540\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    541\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'MLR' object has no attribute 'a'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "56aqEVFWIK5z",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}