{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Seminar 2 PyTorch Tutorial + Text classification with convolutional NNs"
      ],
      "metadata": {
        "id": "-8XXMcZhR-Gk"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H6oqGiIXvrMl"
      },
      "source": [
        "Following resources have been used in preparation of this notebook:\n",
        "* PyTorch Tutorial Notebook, [PyTorch Tutorial](https://colab.research.google.com/drive/1Pz8b_h-W9zIBk1p2e6v-YFYThG1NkYeS?usp=sharing) by Dilara Soylu and Ethan Chi, offered on CS224N course in Stanford"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Please make a copy into your own Drive!"
      ],
      "metadata": {
        "id": "s2jvK3g_2zrK"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4gk1UKaNvrMv"
      },
      "source": [
        "## Introduction\n",
        "[PyTorch](https://pytorch.org/) is a deep learning framework, one of the two main frameworks alongside [TensorFlow](https://www.tensorflow.org/). The installation can be done via Pip or Conda, as described [here](https://pytorch.org/). Let's start by importing PyTorch:"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\\#Question: Why don't we just use Numpy?"
      ],
      "metadata": {
        "id": "vAebKjM4YqxX"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u0ukr7quvrMx"
      },
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "\n",
        "# Import pprint, module we use for making our print statements prettier\n",
        "import pprint\n",
        "pp = pprint.PrettyPrinter()"
      ],
      "execution_count": 88,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Main advantages:\n",
        "1. Automatic Differentiation (Autograd)\n",
        "2. GPU Acceleration\n",
        "3. Built-in Neural Network Modules"
      ],
      "metadata": {
        "id": "VMEmPJHgcjwK"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k10ZRdcBwDP3"
      },
      "source": [
        "We are all set to start our tutorial. Let's dive in!"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Main Modules in PyTorch\n",
        "\n",
        "1.  **`torch`**\n",
        "\n",
        "    This is the base library. It contains the `Tensor` object and a huge number of mathematical functions that operate on Tensors (like `torch.add`, `torch.matmul`, `torch.sigmoid`, etc.). It's the equivalent of the base `numpy` library.\n",
        "\n",
        "2.  **`torch.nn`** (Neural Networks)\n",
        "\n",
        "    This is where the \"Lego Kits\" are. It provides all the building blocks for creating neural networks.\n",
        "\n",
        "    > **Layers:** Pre-built layers like `nn.Linear` (a standard fully-connected layer), `nn.Conv2d` (for images), and `nn.LSTM` (for sequences).\n",
        "    >\n",
        "    > **Loss Functions:** Ways to measure your model's error, like `nn.MSELoss` (Mean Squared Error for regression) or `nn.CrossEntropyLoss` (for classification).\n",
        "    >\n",
        "    > **Containers:** A special class called `nn.Module`. All of your models will be classes that inherit from `nn.Module`. This gives them the ability to track parameters, move to the GPU, and more.\n",
        "\n",
        "3.  **`torch.autograd`**\n",
        "\n",
        "    You rarely use this directly, but it's the engine running under the hood. When you create a tensor with `requires_grad=True`, `autograd` starts building a graph of operations. When you call `.backward()` on a result (like your loss), it travels backward through this graph, calculating the gradients for each parameter.\n",
        "\n",
        "4.  **`torch.optim`** (Optimizers)\n",
        "\n",
        "    This module contains algorithms to update your model's weights based on the gradients calculated by `autograd`. This is the \"how to improve\" part. You give it your model's parameters and a learning rate, and it handles the updates.\n",
        "\n",
        "    **Common optimizers include:** `optim.SGD` (Stochastic Gradient Descent), `optim.Adam`, and `optim.RMSprop`.\n",
        "\n",
        "5.  **`torch.utils.data`**\n",
        "\n",
        "    Deep learning requires a lot of data. This module provides tools to make data loading easy and efficient.\n",
        "\n",
        "    > **`Dataset`:** A class you can use to represent your dataset. You typically implement `__len__` (to return the size) and `__getitem__` (to get a single data point).\n",
        "    >\n",
        "    > **`DataLoader`:** This is a magical utility. You wrap your `Dataset` in a `DataLoader`, and it will automatically handle batching your data, shuffling it, and even loading it in parallel using multiple CPU cores. This prevents your GPU from sitting idle waiting for data."
      ],
      "metadata": {
        "id": "R5kHBOSjoWJ5"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OLdSN9ZXvrM0"
      },
      "source": [
        "##Part 1: Tensors\n",
        "\n",
        "**Tensors** are PyTorch's most basic building block. Each tensor is a multi-dimensional matrix; for example, a 256x256 square image might be represented by a `3x256x256` tensor, where the first dimension represents color. Here's how to create a tensor:\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list_of_lists = [\n",
        "  [1, 2, 3],\n",
        "  [4, 5, 6],\n",
        "]\n",
        "print(list_of_lists)"
      ],
      "metadata": {
        "id": "hXD7cTLTh4oF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "68436f11-8576-4ef9-b0b6-b4448a983571"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[1, 2, 3], [4, 5, 6]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = torch.tensor(list_of_lists)\n",
        "print(data)"
      ],
      "metadata": {
        "id": "G2u7NOqWNJ7c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5474157e-eae4-47d7-a028-a0e594a6499c"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1, 2, 3],\n",
            "        [4, 5, 6]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Initializing a tensor\n",
        "data = torch.tensor([\n",
        "                     [0, 1],\n",
        "                     [2, 3],\n",
        "                     [4, 5]\n",
        "                    ])\n",
        "print(data)"
      ],
      "metadata": {
        "id": "-VLgHhj0n3LM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "58c0ff6f-f0e0-4e0d-ac1a-71306b412cd3"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0, 1],\n",
            "        [2, 3],\n",
            "        [4, 5]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Each tensor has a **data type**: the major data types you'll need to worry about are floats (`torch.float32`) and integers (`torch.int`). You can specify the data type explicitly when you create the tensor:"
      ],
      "metadata": {
        "id": "1i7vrR1_oO4I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Initializing a tensor with an explicit data type\n",
        "# Notice the dots after the numbers, which specify that they're floats\n",
        "data = torch.tensor([\n",
        "                     [0, 1],\n",
        "                     [2, 3],\n",
        "                     [4, 5]\n",
        "                    ], dtype=torch.float32)\n",
        "print(data)"
      ],
      "metadata": {
        "id": "t7nMdqgMoLOa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0ebd8661-0983-49d9-af0e-85d5dce87f0c"
      },
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 1.],\n",
            "        [2., 3.],\n",
            "        [4., 5.]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Initializing a tensor with an explicit data type\n",
        "# Notice the dots after the numbers, which specify that they're floats\n",
        "data = torch.tensor([\n",
        "                     [0.11111111, 1],\n",
        "                     [2, 3],\n",
        "                     [4, 5]\n",
        "                    ], dtype=torch.float32)\n",
        "print(data)"
      ],
      "metadata": {
        "id": "I4vr6EYbiOEJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "37817bdd-58c6-4740-ae73-d126853c0dcd"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0.1111, 1.0000],\n",
            "        [2.0000, 3.0000],\n",
            "        [4.0000, 5.0000]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Initializing a tensor with an explicit data type\n",
        "# Notice the dots after the numbers, which specify that they're floats\n",
        "data = torch.tensor([\n",
        "                     [0.11111111, 1],\n",
        "                     [2, 3],\n",
        "                     [4, 5]\n",
        "                    ])\n",
        "print(data)"
      ],
      "metadata": {
        "id": "jnB8J23WiUTi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "baaeb519-e69b-4ec6-b7e3-196a8c5a4653"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0.1111, 1.0000],\n",
            "        [2.0000, 3.0000],\n",
            "        [4.0000, 5.0000]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "!!! Don't confuse torch.tensor with torch.Tensor.\n",
        "\n",
        "torch.tensor returns tensor with type of input data.\n",
        "\n",
        "torch.Tensor returns tensor with type FloatTensor.\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "YLHy6h9gizy8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Utility functions also exist to create tensors with given shapes and contents:"
      ],
      "metadata": {
        "id": "aiGCmTsrpkP-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "zeros = torch.zeros(2, 5)  # a tensor of all zeros\n",
        "print(zeros)"
      ],
      "metadata": {
        "id": "0tn-N-z_qYj0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7f6ca171-0b2e-4c4f-e2f9-16c82a450517"
      },
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0., 0., 0., 0., 0.],\n",
            "        [0., 0., 0., 0., 0.]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ones = torch.ones(3, 4)   # a tensor of all ones\n",
        "print(ones)"
      ],
      "metadata": {
        "id": "ue26M5Npqoe3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "020c7850-d928-4cf2-b1f0-2662b1bcbdae"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1., 1., 1., 1.],\n",
            "        [1., 1., 1., 1.],\n",
            "        [1., 1., 1., 1.]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rr = torch.arange(1, 10) # range from [1, 10)\n",
        "print(rr)"
      ],
      "metadata": {
        "id": "hdvaujtvqokI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d168407e-7442-4acd-c323-79dcad0c56ef"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([1, 2, 3, 4, 5, 6, 7, 8, 9])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rr + 2"
      ],
      "metadata": {
        "id": "lK3q3LRHipHB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "632aaf9b-72e6-405d-8a06-58c6b41589a7"
      },
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([ 3,  4,  5,  6,  7,  8,  9, 10, 11])"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rr * 2"
      ],
      "metadata": {
        "id": "cDQ-v6AFiyco",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "38729d02-3916-47d9-d3a1-15a89e3e412f"
      },
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([ 2,  4,  6,  8, 10, 12, 14, 16, 18])"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = torch.tensor([[1, 2], [2, 3], [4, 5]])      # (3, 2)\n",
        "b = torch.tensor([[1, 2, 3, 4], [5, 6, 7, 8]])  # (2, 4)\n",
        "\n",
        "print(\"A is\", a)\n",
        "print(\"B is\", b)\n",
        "print(\"The product is\", a.matmul(b)) #(3, 4)\n",
        "print(\"The other product is\", a @ b) # +, -, *, @"
      ],
      "metadata": {
        "id": "OFcjwshvi3pC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "33ccc74b-1111-42ce-f063-2156998a3b2e"
      },
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "A is tensor([[1, 2],\n",
            "        [2, 3],\n",
            "        [4, 5]])\n",
            "B is tensor([[1, 2, 3, 4],\n",
            "        [5, 6, 7, 8]])\n",
            "The product is tensor([[11, 14, 17, 20],\n",
            "        [17, 22, 27, 32],\n",
            "        [29, 38, 47, 56]])\n",
            "The other product is tensor([[11, 14, 17, 20],\n",
            "        [17, 22, 27, 32],\n",
            "        [29, 38, 47, 56]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The **shape** of a matrix (which can be accessed by `.shape`) is defined as the dimensions of the matrix. Here's some examples:"
      ],
      "metadata": {
        "id": "SCS5z1lip9lq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "matr_2d = torch.tensor([[1, 2, 3], [4, 5, 6]])\n",
        "print(matr_2d.shape)\n",
        "print(matr_2d)"
      ],
      "metadata": {
        "id": "fMptIpZkq0da",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "77454999-4945-488f-8765-d4f3d7f09910"
      },
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([2, 3])\n",
            "tensor([[1, 2, 3],\n",
            "        [4, 5, 6]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "matr_3d = torch.tensor([[[1, 2, 3, 4], [-2, 5, 6, 9]], [[5, 6, 7, 2], [8, 9, 10, 4]], [[-3, 2, 2, 1], [4, 6, 5, 9]]])\n",
        "print(matr_3d)\n",
        "print(matr_3d.shape)"
      ],
      "metadata": {
        "id": "aWjD7WjPqC6t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7360d8f7-c1f1-4da5-a585-2180b45114b6"
      },
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[[ 1,  2,  3,  4],\n",
            "         [-2,  5,  6,  9]],\n",
            "\n",
            "        [[ 5,  6,  7,  2],\n",
            "         [ 8,  9, 10,  4]],\n",
            "\n",
            "        [[-3,  2,  2,  1],\n",
            "         [ 4,  6,  5,  9]]])\n",
            "torch.Size([3, 2, 4])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Reshaping** tensors can be used to make batch operations easier (more on that later), but be careful that the data is reshaped in the order you expect:"
      ],
      "metadata": {
        "id": "7wKqP85rrF-P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rr = torch.arange(1, 16)\n",
        "print(\"The shape is currently\", rr.shape)\n",
        "print(\"The contents are currently\", rr)\n",
        "print()\n",
        "rr = rr.view(5, 3)\n",
        "print(\"After reshaping, the shape is currently\", rr.shape)\n",
        "print(\"The contents are currently\", rr)"
      ],
      "metadata": {
        "id": "HmUcqHYUrMu1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe1dd37b-9565-4d28-ccb2-2faf3fcd8cac"
      },
      "execution_count": 103,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The shape is currently torch.Size([15])\n",
            "The contents are currently tensor([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15])\n",
            "\n",
            "After reshaping, the shape is currently torch.Size([5, 3])\n",
            "The contents are currently tensor([[ 1,  2,  3],\n",
            "        [ 4,  5,  6],\n",
            "        [ 7,  8,  9],\n",
            "        [10, 11, 12],\n",
            "        [13, 14, 15]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "!!! Be careful with rr.reshape, it is better to use rr.view."
      ],
      "metadata": {
        "id": "seG6396JjrmM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally, you can also inter-convert tensors with **NumPy arrays**:"
      ],
      "metadata": {
        "id": "GaykBuhoou3M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "# numpy.ndarray --> torch.Tensor:\n",
        "arr = np.array([[1, 0, 5]])\n",
        "data = torch.tensor(arr)\n",
        "print(\"This is a torch.tensor\", data)\n",
        "\n",
        "# torch.Tensor --> numpy.ndarray:\n",
        "new_arr = data.numpy()\n",
        "print(\"This is a np.ndarray\", new_arr)"
      ],
      "metadata": {
        "id": "ppYiPnlko1Ci",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a9cb9ada-ae5b-40dc-f825-1b4289067b32"
      },
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "This is a torch.tensor tensor([[1, 0, 5]])\n",
            "This is a np.ndarray [[1 0 5]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "One of the reasons why we use **tensors** is *vectorized operations*: operations that be conducted in parallel over a particular dimension of a tensor."
      ],
      "metadata": {
        "id": "hyv1l431q9yA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data = torch.arange(1, 36, dtype=torch.float32).reshape(5, 7)\n",
        "print(\"Data is:\", data)\n",
        "\n",
        "# We can perform operations like *sum* over each row...\n",
        "print(\"Taking the sum over rows:\")\n",
        "print(data.sum(dim=1)) #(5,)\n",
        "\n",
        "# or over each column.\n",
        "print(\"Taking thep sum over columns:\")\n",
        "print(data.sum(dim=0)) #(7,)\n",
        "\n",
        "# Other operations are available:\n",
        "print(\"Taking the stdev over rows:\")\n",
        "print(data.std(dim=1))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kas2MEFDsJWk",
        "outputId": "0831fa60-867e-42c3-9821-00d75cc63219"
      },
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data is: tensor([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
            "        [ 8.,  9., 10., 11., 12., 13., 14.],\n",
            "        [15., 16., 17., 18., 19., 20., 21.],\n",
            "        [22., 23., 24., 25., 26., 27., 28.],\n",
            "        [29., 30., 31., 32., 33., 34., 35.]])\n",
            "Taking the sum over rows:\n",
            "tensor([ 28.,  77., 126., 175., 224.])\n",
            "Taking thep sum over columns:\n",
            "tensor([ 75.,  80.,  85.,  90.,  95., 100., 105.])\n",
            "Taking the stdev over rows:\n",
            "tensor([2.1602, 2.1602, 2.1602, 2.1602, 2.1602])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = torch.arange(1, 7, dtype=torch.float32).reshape(1, 2, 3)\n",
        "print(data)\n",
        "print(data.sum(dim=0).sum(dim=0))\n",
        "print(data.sum(dim=0).sum(dim=0).shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g1ByKJL_WYWv",
        "outputId": "167a72af-cc62-4000-8278-074c9602edaa"
      },
      "execution_count": 106,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[[1., 2., 3.],\n",
            "         [4., 5., 6.]]])\n",
            "tensor([5., 7., 9.])\n",
            "torch.Size([3])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.sum()"
      ],
      "metadata": {
        "id": "NPRy-xtuk2tK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d5430257-7fb0-45c8-c0d0-5c2a94a119a9"
      },
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor(21.)"
            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V7BMktFFAkRA"
      },
      "source": [
        "**Indexing**\n",
        "\n",
        "You can access arbitrary elements of a tensor using the `[]` operator."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fRJN7ovWDsKV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a3e0db93-b9ce-441f-99e2-68f24e1083d9"
      },
      "source": [
        "# Initialize an example tensor\n",
        "x = torch.Tensor([\n",
        "                  [[1, 2], [3, 4]],\n",
        "                  [[5, 6], [7, 8]],\n",
        "                  [[9, 10], [11, 12]]\n",
        "                 ])\n",
        "x"
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[ 1.,  2.],\n",
              "         [ 3.,  4.]],\n",
              "\n",
              "        [[ 5.,  6.],\n",
              "         [ 7.,  8.]],\n",
              "\n",
              "        [[ 9., 10.],\n",
              "         [11., 12.]]])"
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M67ZiOF1Heyc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9266f45d-e21c-4ad2-8baf-b4fdd031f8ca"
      },
      "source": [
        "x.shape"
      ],
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([3, 2, 2])"
            ]
          },
          "metadata": {},
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "guXKE7m8AX1K",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7a53e748-4e18-4656-f4cd-25029706b3ac"
      },
      "source": [
        "# Access the 0th element, which is the first row\n",
        "x[0] # Equivalent to x[0, :]"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[1., 2.],\n",
              "        [3., 4.]])"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x[:, 0]"
      ],
      "metadata": {
        "id": "zn4pW2rkmXuj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f7d881a1-dac1-4062-9fed-de931dee6e24"
      },
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[ 1.,  2.],\n",
              "        [ 5.,  6.],\n",
              "        [ 9., 10.]])"
            ]
          },
          "metadata": {},
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g8m8EyVvES4-"
      },
      "source": [
        "We can also index into multiple dimensions with `:`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2Z6GFUcuEL85",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c64b5964-a6bf-40c2-e9e0-6f632d04d62c"
      },
      "source": [
        "# Get the top left element of each element in our tensor\n",
        "x[:, 0, 0]"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([1., 5., 9.])"
            ]
          },
          "metadata": {},
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x[:, :, :]"
      ],
      "metadata": {
        "id": "TRkMhiJNnWAt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7b9da574-8efe-4cf7-907a-d9dfb8fc8c8b"
      },
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[ 1.,  2.],\n",
              "         [ 3.,  4.]],\n",
              "\n",
              "        [[ 5.,  6.],\n",
              "         [ 7.,  8.]],\n",
              "\n",
              "        [[ 9., 10.],\n",
              "         [11., 12.]]])"
            ]
          },
          "metadata": {},
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rm8vc3nuXaEw"
      },
      "source": [
        "We can also access arbitrary elements in each dimension."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R4xl6CW3RrEw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f72eb525-1040-444e-a0b7-9a1299cab845"
      },
      "source": [
        "# Let's access the 0th and 1st elements, each twice\n",
        "# same as stacking x[0], x[0], x[1], x[1]\n",
        "i = torch.tensor([0, 0, 1, 1])\n",
        "x[i]"
      ],
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[1., 2.],\n",
              "         [3., 4.]],\n",
              "\n",
              "        [[1., 2.],\n",
              "         [3., 4.]],\n",
              "\n",
              "        [[5., 6.],\n",
              "         [7., 8.]],\n",
              "\n",
              "        [[5., 6.],\n",
              "         [7., 8.]]])"
            ]
          },
          "metadata": {},
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A3QYZ8k7Wvqp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b4c6f0e0-45b3-4a88-ce02-3142495cef33"
      },
      "source": [
        "# Let's access the 0th elements of the 1st and 2nd elements\n",
        "\n",
        "i = torch.tensor([1, 2])\n",
        "j = torch.tensor([0])\n",
        "x[i, j]"
      ],
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[ 5.,  6.],\n",
              "        [ 9., 10.]])"
            ]
          },
          "metadata": {},
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WAELXC--IHS7"
      },
      "source": [
        "We can get a `Python` scalar value from a tensor with `item()`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BM-ZujN2IGaQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe031618-3d3a-470f-ac2d-4edca9838355"
      },
      "source": [
        "x[0, 0, 0]"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor(1.)"
            ]
          },
          "metadata": {},
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6NwxK7d_Ycgs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "422c487f-6099-4910-a1f7-31d3bafd3a0b"
      },
      "source": [
        "x[0, 0, 0].item()"
      ],
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Exercise:\n",
        "\n",
        "Write code that creates a `torch.tensor` with the following contents:\n",
        "$\\begin{bmatrix} 1 & 2.2 & 9.6 \\\\ 4 & -7.2 & 6.3 \\end{bmatrix}$\n",
        "\n",
        "How do you get the first column? The first row?\n",
        "\n"
      ],
      "metadata": {
        "id": "bGod5kHa6OOF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Your code\n"
      ],
      "metadata": {
        "id": "GzREtljlk33-"
      },
      "execution_count": 118,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Re8xiL37eAja"
      },
      "source": [
        "## Autograd\n",
        "Pytorch is well-known for its automatic differentiation feature. We can call the `backward()` method to ask `PyTorch` to calculate the gradients, which are then stored in the `grad` attribute."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-oEvBJHWfn8H",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f0f72cad-7449-4956-aad5-557a917e57d7"
      },
      "source": [
        "# Create an example tensor\n",
        "# requires_grad parameter tells PyTorch to store gradients\n",
        "x = torch.tensor([2.], requires_grad=True)\n",
        "\n",
        "# Print the gradient if it is calculated\n",
        "# Currently None since x is a scalar\n",
        "pp.pprint(x.grad)"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DTJazZXkgthP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9be88bfa-5a4a-4e5b-c573-968e8d382de9"
      },
      "source": [
        "# Calculating the gradient of y with respect to x\n",
        "y = x * x * 3 # 3x^2\n",
        "y.backward()\n",
        "pp.pprint(x.grad)"
      ],
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([12.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Hqc2oM3iV6a"
      },
      "source": [
        "Let's run backprop from a different tensor again to see what happens."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K--Az0Xiic_z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "917d5d7a-2a62-44f4-c6b9-62970b83912a"
      },
      "source": [
        "z = x * x * 3 # 3x^2\n",
        "z.backward()\n",
        "pp.pprint(x.grad)"
      ],
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([24.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "What just happened?"
      ],
      "metadata": {
        "id": "a5iSbie_lMo5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x.grad = None\n",
        "z = x * x * 3 # 3x^2\n",
        "z.backward()\n",
        "# y = x * x * 3\n",
        "pp.pprint(x.grad)"
      ],
      "metadata": {
        "id": "4tIa4dw6Tmar",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "299d19c9-b96d-4f2b-ff32-a55544a750d5"
      },
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([12.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z = x * x * 3 # 3x^2\n",
        "z.backward()\n",
        "# y = x * x * 3\n",
        "pp.pprint(x.grad)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pbyr-P4rdJ9b",
        "outputId": "dd8a1387-cf80-4947-f086-d16e399067a3"
      },
      "execution_count": 123,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([24.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z = x * x * 3 # 3x^2\n",
        "z.backward()\n",
        "# y = x * x * 3\n",
        "pp.pprint(x.grad)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WpvRq_wUdM5y",
        "outputId": "93fb161b-f11e-4a48-a58a-11888455acf7"
      },
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([36.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HhjPkiE6i7ja"
      },
      "source": [
        "We can see that the `x.grad` is updated to be the sum of the gradients calculated so far. When we run backprop in a neural network, we sum up all the gradients for a particular neuron before making an update. This is exactly what is happening here! This is also the reason why we need to run `zero_grad()` in every training iteration (more on this later). Otherwise our gradients would keep building up from one training iteration to the other, which would cause our updates to be wrong."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "ZF8-qyRsneQB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "F_O6veZJnkKk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Please, watch a [video](https://vk.com/video-155161349_456239205) in RUSSIAN about backpropagation if you don't understand it."
      ],
      "metadata": {
        "id": "HW9wKEcb2e_6"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pYLWqKIoaOyd"
      },
      "source": [
        "## Neural Network Module\n",
        "\n",
        "So far we have looked into the tensors, their properties and basic operations on tensors. These are especially useful to get familiar with if we are building the layers of our network from scratch. We will use predefined blocks in the `torch.nn` module of `PyTorch`. We will then put together these blocks to create complex networks. Let's start by importing this module with an alias so that we don't have to type `torch` every time we use it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qUmrDpbhV4Tn"
      },
      "source": [
        "import torch.nn as nn\n",
        "import torch"
      ],
      "execution_count": 125,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "joGvRWjEbak0"
      },
      "source": [
        "### **Linear Layer**\n",
        "We can use `nn.Linear(H_in, H_out)` to create a a linear layer. This will take a matrix of `(N, *, H_in)` dimensions and output a matrix of `(N, *, H_out)`. The `*` denotes that there could be arbitrary number of dimensions in between. The linear layer performs the operation `Ax+b`, where `A` and `b` are initialized randomly. If we don't want the linear layer to learn the bias parameters, we can initialize our layer with `bias=False`."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "Gzkofwno0EU4"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6XfnKI4-a5j9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "386a726a-ac15-44bc-d0ed-9eb115e580d5"
      },
      "source": [
        "# Create the inputs\n",
        "input = torch.ones(2,3,4)\n",
        "# N* H_in -> N*H_out\n",
        "\n",
        "\n",
        "# Make a linear layers transforming N,*,H_in dimensinal inputs to N,*,H_out\n",
        "# dimensional outputs\n",
        "# Your code\n",
        "linear = nn.Linear(4, 2)\n",
        "linear_output = linear(input)\n",
        "linear_output"
      ],
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545]],\n",
              "\n",
              "        [[-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545]]], grad_fn=<ViewBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 126
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "linear_output.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ao4XddjxeBVJ",
        "outputId": "74980ee4-2080-4944-c3f5-2c9670082a88"
      },
      "execution_count": 127,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([2, 3, 2])"
            ]
          },
          "metadata": {},
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0_9XKtAFYpdI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "33162c47-5e9e-4899-8e1a-c81b03c09adb"
      },
      "source": [
        "list(linear.parameters()) # Ax + b"
      ],
      "execution_count": 128,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Parameter containing:\n",
              " tensor([[-0.0714,  0.1831,  0.1683, -0.4080],\n",
              "         [ 0.3401,  0.1907, -0.2754,  0.0613]], requires_grad=True),\n",
              " Parameter containing:\n",
              " tensor([-0.1342, -0.0622], requires_grad=True)]"
            ]
          },
          "metadata": {},
          "execution_count": 128
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Data of shape [batch_size, feature_dim] # 4\n",
        "# [batch_size, output_dim] # 2\n",
        "\n",
        "# linear layer of shape (feature_dim, output_dim)"
      ],
      "metadata": {
        "id": "FsyBaqzZppS8"
      },
      "execution_count": 129,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jAXCCu9keUlW"
      },
      "source": [
        "### **Other Module Layers**\n",
        "There are several other preconfigured layers in the `nn` module. Some commonly used examples are `nn.Conv2d`, `nn.ConvTranspose2d`, `nn.BatchNorm1d`, `nn.BatchNorm2d`, `nn.Upsample` and `nn.MaxPool2d` among many others. We will learn more about these as we progress in the course. For now, the only important thing to remember is that we can treat each of these layers as plug and play components: we will be providing the required dimensions and `PyTorch` will take care of setting them up."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yslDOK66fYWn"
      },
      "source": [
        "### **Activation Function Layer**\n",
        "We can also use the `nn` module to apply activations functions to our tensors. Activation functions are used to add non-linearity to our network. Some examples of activations functions are `nn.ReLU()`, `nn.Sigmoid()` and `nn.LeakyReLU()`. Activation functions operate on each element seperately, so the shape of the tensors we get as an output are the same as the ones we pass in."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IrJP5CveeOON",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6c188890-68d6-42ea-d789-76597764e591"
      },
      "source": [
        "linear_output"
      ],
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545]],\n",
              "\n",
              "        [[-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545],\n",
              "         [-0.2622,  0.2545]]], grad_fn=<ViewBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W9v5FjQtd4Ck",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "559e2611-dc3b-4161-f9b6-5097b33a72df"
      },
      "source": [
        "sigmoid = nn.Sigmoid()\n",
        "output = sigmoid(linear_output)\n",
        "output"
      ],
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[0.4348, 0.5633],\n",
              "         [0.4348, 0.5633],\n",
              "         [0.4348, 0.5633]],\n",
              "\n",
              "        [[0.4348, 0.5633],\n",
              "         [0.4348, 0.5633],\n",
              "         [0.4348, 0.5633]]], grad_fn=<SigmoidBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "![image.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "B0hIsryS0rNG"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RiYTthJwhEYT"
      },
      "source": [
        "### **Putting the Layers Together**\n",
        "So far we have seen that we can create layers and pass the output of one as the input of the next. Instead of creating intermediate tensors and passing them around, we can use `nn.Sequentual`, which does exactly that."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xtJeOqLxhBLY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a1b62aca-817f-44a9-def1-4ce1472cf1ee"
      },
      "source": [
        "block = nn.Sequential(\n",
        "    nn.Linear(4, 2),\n",
        "    nn.Sigmoid()\n",
        ")\n",
        "\n",
        "input = torch.ones(2,3,4)\n",
        "output = block(input)\n",
        "output"
      ],
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[[0.4123, 0.5486],\n",
              "         [0.4123, 0.5486],\n",
              "         [0.4123, 0.5486]],\n",
              "\n",
              "        [[0.4123, 0.5486],\n",
              "         [0.4123, 0.5486],\n",
              "         [0.4123, 0.5486]]], grad_fn=<SigmoidBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GkJ81p3GUVPM"
      },
      "source": [
        "### Custom Modules\n",
        "\n",
        "Instead of using the predefined modules, we can also build our own by extending the `nn.Module` class. For example, we can build a the `nn.Linear` (which also extends `nn.Module`) on our own using the tensor introduced earlier! We can also build new, more complex modules, such as a custom neural network. You will be practicing these in the later assignment.\n",
        "\n",
        "To create a custom module, the first thing we have to do is to extend the `nn.Module`. We can then initialize our parameters in the `__init__` function, starting with a call to the `__init__` function of the super class. All the class attributes we define which are `nn` module objects are treated as parameters, which can be learned during the training. Tensors are not parameters, but they can be turned into parameters if they are wrapped in `nn.Parameter` class.\n",
        "\n",
        "All classes extending `nn.Module` are also expected to implement a `forward(x)` function, where `x` is a tensor. This is the function that is called when a parameter is passed to our module, such as in `model(x)`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J2P7eZiMj32_"
      },
      "source": [
        "class MultilayerPerceptron(nn.Module):\n",
        "\n",
        "  def __init__(self, input_size, hidden_size):\n",
        "    # Call to the __init__ function of the super class\n",
        "    super().__init__()\n",
        "\n",
        "    # Bookkeeping: Saving the initialization parameters\n",
        "    self.input_size = input_size\n",
        "    self.hidden_size = hidden_size\n",
        "\n",
        "    # Defining of our model\n",
        "    # There isn't anything specific about the naming of `self.model`. It could\n",
        "    # be something arbitrary.\n",
        "    self.model = nn.Sequential(\n",
        "        nn.Linear(self.input_size, self.hidden_size),\n",
        "        nn.ReLU(),\n",
        "        nn.Linear(self.hidden_size, self.input_size),\n",
        "        nn.Sigmoid()\n",
        "    )\n",
        "\n",
        "  def forward(self, x):\n",
        "    output = self.model(x)\n",
        "    return output"
      ],
      "execution_count": 133,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b2DrfLiBVjNT"
      },
      "source": [
        "Here is an alternative way to define the same class. You can see that we can replace `nn.Sequential` by defining the individual layers in the `__init__` method and connecting the in the `forward` method."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9-lqhsqwViIk"
      },
      "source": [
        "class MultilayerPerceptron(nn.Module):\n",
        "\n",
        "  def __init__(self, input_size, hidden_size):\n",
        "    # Call to the __init__ function of the super class\n",
        "    super().__init__()\n",
        "\n",
        "    # Bookkeeping: Saving the initialization parameters\n",
        "    self.input_size = input_size\n",
        "    self.hidden_size = hidden_size\n",
        "\n",
        "    # Defining of our layers\n",
        "    self.linear = nn.Linear(self.input_size, self.hidden_size)\n",
        "    self.relu = nn.ReLU()\n",
        "    self.linear2 = nn.Linear(self.hidden_size, self.input_size)\n",
        "    self.sigmoid = nn.Sigmoid()\n",
        "\n",
        "  def forward(self, x):\n",
        "    linear = self.linear(x)\n",
        "    relu = self.relu(linear)\n",
        "    linear2 = self.linear2(relu)\n",
        "    output = self.sigmoid(linear2)\n",
        "    return output"
      ],
      "execution_count": 134,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YQelcFo5bXgU"
      },
      "source": [
        "Now that we have defined our class, we can instantiate it and see what it does."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cXi0T0FZbV0y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5e0af8ab-268f-4509-dde8-0fc48615371d"
      },
      "source": [
        "# Make a sample input\n",
        "input = torch.randn(2, 5)\n",
        "\n",
        "# Create our model\n",
        "model = MultilayerPerceptron(5, 3)\n",
        "\n",
        "# Pass our input through our model\n",
        "model(input)"
      ],
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[0.6085, 0.4179, 0.4451, 0.5120, 0.3183],\n",
              "        [0.5690, 0.4108, 0.4707, 0.4472, 0.3213]], grad_fn=<SigmoidBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tCCbjc-Fb2-B"
      },
      "source": [
        "We can inspect the parameters of our model with `named_parameters()` and `parameters()` methods."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7d23soYIb2WZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "de2e95bd-e655-450e-d9d7-f23a31249abb"
      },
      "source": [
        "list(model.named_parameters())"
      ],
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('linear.weight',\n",
              "  Parameter containing:\n",
              "  tensor([[ 0.3389, -0.3912,  0.2910,  0.0710, -0.3517],\n",
              "          [-0.0409,  0.3221,  0.3916, -0.1141, -0.2853],\n",
              "          [-0.2538,  0.3420, -0.1027,  0.3690,  0.0661]], requires_grad=True)),\n",
              " ('linear.bias',\n",
              "  Parameter containing:\n",
              "  tensor([ 0.2253, -0.1155, -0.2242], requires_grad=True)),\n",
              " ('linear2.weight',\n",
              "  Parameter containing:\n",
              "  tensor([[ 0.3321,  0.2718, -0.3528],\n",
              "          [ 0.0791, -0.1085, -0.4380],\n",
              "          [-0.4464, -0.2594, -0.0722],\n",
              "          [ 0.3156,  0.5287, -0.3990],\n",
              "          [-0.4244, -0.1052, -0.3077]], requires_grad=True)),\n",
              " ('linear2.bias',\n",
              "  Parameter containing:\n",
              "  tensor([ 0.1033, -0.3021,  0.1666, -0.4444, -0.4833], requires_grad=True))]"
            ]
          },
          "metadata": {},
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x5JegycOdMFy"
      },
      "source": [
        "## Optimization\n",
        "We have showed how gradients are calculated with the `backward()` function. Having the gradients isn't enought for our models to learn. We also need to know how to update the parameters of our models. This is where the optomozers comes in. `torch.optim` module contains several optimizers that we can use. Some popular examples are `optim.SGD` and `optim.Adam`. When initializing optimizers, we pass our model parameters, which can be accessed with `model.parameters()`, telling the optimizers which values it will be optimizing. Optimizers also has a learning rate (`lr`) parameter, which determines how big of an update will be made in every step. Different optimizers have different hyperparameters as well."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W0F-TvV0kk-I"
      },
      "source": [
        "import torch.optim as optim"
      ],
      "execution_count": 137,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wgak6o5dlQWF"
      },
      "source": [
        "After we have our optimization function, we can define a `loss` that we want to optimize for. We can either define the loss ourselves, or use one of the predefined loss function in `PyTorch`, such as `nn.BCELoss()`. Let's put everything together now! We will start by creating some dummy data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dGYFiaT_vXBn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb09d6d5-3603-45df-d2f6-82d1b6aa175f"
      },
      "source": [
        "# Create the y data\n",
        "y = torch.ones(10, 5)\n",
        "\n",
        "# Add some noise to our goal y to generate our x\n",
        "# We want out model to predict our original data, albeit the noise\n",
        "x = y + torch.randn_like(y)\n",
        "x"
      ],
      "execution_count": 138,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[ 1.3765, -0.6371,  0.4273,  1.7571,  0.5002],\n",
              "        [ 2.3304,  2.1821,  0.9149,  0.3020,  1.4407],\n",
              "        [ 0.9951,  1.1213,  0.3425, -0.0546,  0.4395],\n",
              "        [ 2.4713,  1.3027,  1.1747,  1.1209,  2.8363],\n",
              "        [ 2.3774,  2.0263,  2.5719,  1.3411, -0.2954],\n",
              "        [ 2.3347, -0.1992,  1.4411,  2.8139,  1.5296],\n",
              "        [ 0.4137,  2.2070,  1.4053,  1.4150,  1.5568],\n",
              "        [ 1.8883, -0.4805,  0.5026, -0.7640, -0.2618],\n",
              "        [-0.7256,  0.3107, -1.0429,  0.7204,  1.3239],\n",
              "        [ 0.2710,  0.0540,  1.1841,  1.4047,  0.9001]])"
            ]
          },
          "metadata": {},
          "execution_count": 138
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BEsiOdpWvfLj"
      },
      "source": [
        "Now, we can define our model, optimizer and the loss function."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2oA2XsdsbN8p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "abcc1f40-4baf-4da4-dcb2-fc889edf31ba"
      },
      "source": [
        "# Instantiate the model\n",
        "model = MultilayerPerceptron(5, 3)\n",
        "\n",
        "# Define the optimizer\n",
        "adam = optim.Adam(model.parameters(), lr=1e-1)\n",
        "\n",
        "# Define loss using a predefined loss function\n",
        "loss_function = nn.MSELoss()\n",
        "\n",
        "# Calculate how our model is doing now\n",
        "y_pred = model(x)\n",
        "loss_function(y_pred, y).item()"
      ],
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.25423458218574524"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gtxU7Y8ZufSR"
      },
      "source": [
        "Let's see if we can have our model achieve a smaller loss. Now that we have everything we need, we can setup our training loop."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ogl6-Ctmuek6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "74b2b737-7f47-4f23-a33e-7b35a6284f78"
      },
      "source": [
        "# Set the number of epoch, which determines the number of training iterations\n",
        "n_epoch = 10\n",
        "\n",
        "for epoch in range(n_epoch):\n",
        "  # Set the gradients to 0\n",
        "  adam.zero_grad()\n",
        "\n",
        "  # Get the model predictions\n",
        "  y_pred = model(x)\n",
        "\n",
        "  # Get the loss\n",
        "  loss = loss_function(y_pred, y)\n",
        "\n",
        "  # Print stats\n",
        "  print(f\"Epoch {epoch}: traing loss: {loss}\")\n",
        "\n",
        "  # Compute the gradients\n",
        "  loss.backward()\n",
        "\n",
        "  # Take a step to optimize the weights\n",
        "  adam.step()\n"
      ],
      "execution_count": 140,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 0: traing loss: 0.25423458218574524\n",
            "Epoch 1: traing loss: 0.16594503819942474\n",
            "Epoch 2: traing loss: 0.10688162595033646\n",
            "Epoch 3: traing loss: 0.06441553682088852\n",
            "Epoch 4: traing loss: 0.037539880722761154\n",
            "Epoch 5: traing loss: 0.022610673680901527\n",
            "Epoch 6: traing loss: 0.013234150595963001\n",
            "Epoch 7: traing loss: 0.007887506857514381\n",
            "Epoch 8: traing loss: 0.004699023440480232\n",
            "Epoch 9: traing loss: 0.002766030142083764\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZrMJ8AmqeCY-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "742c0799-0cc5-4665-9f37-3854d72d522f"
      },
      "source": [
        "list(model.parameters())"
      ],
      "execution_count": 141,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Parameter containing:\n",
              " tensor([[-0.7748, -0.5615, -0.7180, -0.1349, -0.1135],\n",
              "         [ 0.6640,  1.0794,  0.5088,  0.7678,  1.1414],\n",
              "         [-0.0971, -0.3012, -0.2938, -0.6451, -0.2888]], requires_grad=True),\n",
              " Parameter containing:\n",
              " tensor([-0.1102,  0.9180, -0.6533], requires_grad=True),\n",
              " Parameter containing:\n",
              " tensor([[ 0.0715,  0.8658,  0.0584],\n",
              "         [ 0.3302,  1.3070,  0.6598],\n",
              "         [ 0.7756,  0.6355,  0.8676],\n",
              "         [ 0.1177,  1.1509, -0.0585],\n",
              "         [ 0.0644,  1.2784,  0.4249]], requires_grad=True),\n",
              " Parameter containing:\n",
              " tensor([1.1453, 1.2909, 1.2211, 0.5447, 0.7458], requires_grad=True)]"
            ]
          },
          "metadata": {},
          "execution_count": 141
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4nXApd82wlsF"
      },
      "source": [
        "You can see that our loss is decreasing. Let's check the predictions of our model now and see if they are close to our original `y`, which was all `1s`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gRqE7P9EtvuS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6f6daf7a-3e06-4b10-b39d-ca1bbe0c1da8"
      },
      "source": [
        "# See how our model performs on the training data\n",
        "y_pred = model(x)\n",
        "y_pred"
      ],
      "execution_count": 142,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[0.9818, 0.9962, 0.9647, 0.9869, 0.9929],\n",
              "        [0.9994, 1.0000, 0.9969, 0.9998, 0.9999],\n",
              "        [0.9838, 0.9969, 0.9676, 0.9888, 0.9941],\n",
              "        [0.9998, 1.0000, 0.9988, 1.0000, 1.0000],\n",
              "        [0.9990, 1.0000, 0.9958, 0.9997, 0.9999],\n",
              "        [0.9992, 1.0000, 0.9963, 0.9998, 0.9999],\n",
              "        [0.9994, 1.0000, 0.9969, 0.9998, 0.9999],\n",
              "        [0.8841, 0.9327, 0.8666, 0.8485, 0.8864],\n",
              "        [0.9607, 0.9897, 0.9641, 0.9641, 0.9769],\n",
              "        [0.9889, 0.9982, 0.9753, 0.9933, 0.9966]], grad_fn=<SigmoidBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IJng31_Pi2R6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a8138deb-7411-4cf2-e8df-a1db2c67ebfe"
      },
      "source": [
        "# Create test data and check how our model performs on it\n",
        "x2 = y + torch.randn_like(y)\n",
        "y_pred = model(x2)\n",
        "y_pred"
      ],
      "execution_count": 143,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[0.9817, 0.9962, 0.9645, 0.9868, 0.9928],\n",
              "        [0.9907, 0.9987, 0.9783, 0.9947, 0.9974],\n",
              "        [0.9970, 0.9998, 0.9906, 0.9988, 0.9995],\n",
              "        [0.9975, 0.9998, 0.9916, 0.9991, 0.9996],\n",
              "        [0.9902, 0.9985, 0.9775, 0.9943, 0.9972],\n",
              "        [0.9980, 0.9999, 0.9928, 0.9993, 0.9997],\n",
              "        [0.9750, 0.9939, 0.9556, 0.9800, 0.9886],\n",
              "        [0.9996, 1.0000, 0.9977, 0.9999, 1.0000],\n",
              "        [0.9986, 0.9999, 0.9945, 0.9996, 0.9998],\n",
              "        [0.9990, 1.0000, 0.9956, 0.9997, 0.9999]], grad_fn=<SigmoidBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8WNk6oIZw2xo"
      },
      "source": [
        "Great! Looks like our model almost perfectly learned to filter out the noise from the `x` that we passed in!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ak0lZQ89qgmX"
      },
      "source": [
        "## Demo: Sentence Classification with CNNs\n",
        "\n",
        "Until this part of the notebook, we have learned the fundamentals of PyTorch and built a basic network solving a toy task. Now we will attempt to solve an example NLP task. Here are the things we will learn:\n",
        "\n",
        "1. Data: Creating a Dataset of Batched Tensors\n",
        "2. Modeling\n",
        "3. Training\n",
        "4. Prediction\n",
        "\n",
        "In this section, our goal will be to train a model that will find if there is mentioned a `LOCATION` in a sentence or not."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4dDv1DMgqgmY"
      },
      "source": [
        "### Data\n",
        "\n",
        "The very first task of any machine learning project is to set up our training set. Usually, there will be a training corpus we will be utilizing. In NLP tasks, the corpus would generally be a `.txt` or `.csv` file where each row corresponds to a sentence or a tabular datapoint. In our toy task, we will assume that we have already read our data and the corresponding labels into a `Python` list."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "import torch.nn as nn"
      ],
      "metadata": {
        "id": "s7wN2KquqgmZ"
      },
      "execution_count": 144,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hsrB1rYQqgmZ"
      },
      "source": [
        "# Our raw data, which consists of sentences\n",
        "corpus = [\n",
        "          \"We always come to Paris\",\n",
        "          \"The professor is from Australia\",\n",
        "          \"I live in Stanford\",\n",
        "          \"He comes from Taiwan\",\n",
        "          \"The capital of Turkey is Ankara\",\n",
        "          \"I like icecream\",\n",
        "          \"The wind is strong today\",\n",
        "          \"Silly Sally sells sea shells\"\n",
        "         ]"
      ],
      "execution_count": 145,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JU1e0ObNqgmb"
      },
      "source": [
        "#### Preprocessing\n",
        "\n",
        "To make it easier for our models to learn, we usually apply a few preprocessing steps to our data. This is especially important when dealing with text data. Here are some examples of text preprocessing:\n",
        "* **Tokenization**: Tokenizing the sentences into words.\n",
        "* **Lowercasing**: Changing all the letters to be lowercase.\n",
        "* **Noise removal:** Removing special characters (such as punctuations).\n",
        "* **Stop words removal**: Removing commonly used words.\n",
        "\n",
        "Which preprocessing steps are necessary is determined by the task at hand. For example, although it is useful to remove special characters in some tasks, for others they may be important (for example, if we are dealing with multiple languages). For our task, we will lowercase our words and tokenize.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c2bce57a-625d-45bc-f44d-50b3200df423",
        "id": "8CP5MOTKqgmb"
      },
      "source": [
        "# The preprocessing function we will use to generate our training examples\n",
        "# Our function is a simple one, we lowercase the letters\n",
        "# and then tokenize the words.\n",
        "def preprocess_sentence(sentence):\n",
        "  return sentence.lower().split()\n",
        "\n",
        "# Create our training set\n",
        "train_sentences = [preprocess_sentence(sent) for sent in corpus]\n",
        "train_sentences"
      ],
      "execution_count": 146,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['we', 'always', 'come', 'to', 'paris'],\n",
              " ['the', 'professor', 'is', 'from', 'australia'],\n",
              " ['i', 'live', 'in', 'stanford'],\n",
              " ['he', 'comes', 'from', 'taiwan'],\n",
              " ['the', 'capital', 'of', 'turkey', 'is', 'ankara'],\n",
              " ['i', 'like', 'icecream'],\n",
              " ['the', 'wind', 'is', 'strong', 'today'],\n",
              " ['silly', 'sally', 'sells', 'sea', 'shells']]"
            ]
          },
          "metadata": {},
          "execution_count": 146
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mVpLRA1pqgmc"
      },
      "source": [
        "For each training example we have, we should also have a corresponding label. Recall that the goal of our model was to determine if  there is a mention of a `LOCATION` in a sentence. That is, we want our model to output `0` for all sentences where there are no `LOCATION`s and `1` otherwise."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CpMW5Fh6qgmc",
        "outputId": "2eb8d2c2-98a6-4965-93cc-c4c2da7bcd2a"
      },
      "source": [
        "# Set of locations that appear in our corpus\n",
        "locations = set([\"australia\", \"ankara\", \"paris\", \"stanford\", \"taiwan\", \"turkey\"])\n",
        "\n",
        "# Our train labels\n",
        "train_labels = [[1 if word in locations else 0 for word in sent] for sent in train_sentences]\n",
        "print(train_labels)\n",
        "train_labels = [max(sent) for sent in train_labels]\n",
        "train_labels"
      ],
      "execution_count": 147,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0, 0, 0, 0, 1], [0, 0, 0, 0, 1], [0, 0, 0, 1], [0, 0, 0, 1], [0, 0, 0, 1, 0, 1], [0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[1, 1, 1, 1, 1, 0, 0, 0]"
            ]
          },
          "metadata": {},
          "execution_count": 147
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fho4L9ENqgmd"
      },
      "source": [
        "#### Converting Words to Embeddings\n",
        "\n",
        "Let's look at our training data a little more closely. Each datapoint we have is a sequence of words. On the other hand, we know that machine learning models work with numbers in vectors. How are we going to turn words into numbers? You may be thinking embeddings and you are right!\n",
        "\n",
        "Imagine that we have an embedding lookup table `E`, where each row corresponds to an embedding. That is, each word in our vocabulary would have a corresponding embedding row `i` in this table. Whenever we want to find an embedding for a word, we will follow these steps:\n",
        "1. Find the corresponding index `i` of the word in the embedding table: `word->index`.\n",
        "2. Index into the embedding table and get the embedding: `index->embedding`.\n",
        "\n",
        "Let's look at the first step. We should assign all the words in our vocabulary to a corresponding index. We can do it as follows:\n",
        "1. Find all the unique words in our corpus.\n",
        "2. Assign an index to each."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gjp5Bzqqqgmd",
        "outputId": "b23490a0-90f3-4cc7-c2b6-ead3d8576bf3"
      },
      "source": [
        "# Find all the unique words in our corpus\n",
        "vocabulary = set(w for s in train_sentences for w in s)\n",
        "vocabulary"
      ],
      "execution_count": 148,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'always',\n",
              " 'ankara',\n",
              " 'australia',\n",
              " 'capital',\n",
              " 'come',\n",
              " 'comes',\n",
              " 'from',\n",
              " 'he',\n",
              " 'i',\n",
              " 'icecream',\n",
              " 'in',\n",
              " 'is',\n",
              " 'like',\n",
              " 'live',\n",
              " 'of',\n",
              " 'paris',\n",
              " 'professor',\n",
              " 'sally',\n",
              " 'sea',\n",
              " 'sells',\n",
              " 'shells',\n",
              " 'silly',\n",
              " 'stanford',\n",
              " 'strong',\n",
              " 'taiwan',\n",
              " 'the',\n",
              " 'to',\n",
              " 'today',\n",
              " 'turkey',\n",
              " 'we',\n",
              " 'wind'}"
            ]
          },
          "metadata": {},
          "execution_count": 148
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aR8Ca_snqgmd"
      },
      "source": [
        "`vocabulary` now contains all the words in our corpus. On the other hand, during the test time, we can see words that are not contained in our vocabulary. If we can figure out a way to represent the unknown words, our model can still reason about whether they are a `LOCATION` or not, since we are also looking at the neighboring words for each prediction.\n",
        "\n",
        "We introduce a special token, `<unk>`, to tackle the words that are out of vocabulary. We could pick another string for our unknown token if we wanted. The only requirement here is that our token should be unique: we should only be using this token for unknown words. We will also add this special token to our vocabulary."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aAqymGNOqgmd",
        "outputId": "4bc3852e-281d-4850-c824-af6d28faa2c1"
      },
      "source": [
        "# Add the unknown token to our vocabulary\n",
        "vocabulary.add(\"<unk>\")\n",
        "vocabulary"
      ],
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'<unk>',\n",
              " 'always',\n",
              " 'ankara',\n",
              " 'australia',\n",
              " 'capital',\n",
              " 'come',\n",
              " 'comes',\n",
              " 'from',\n",
              " 'he',\n",
              " 'i',\n",
              " 'icecream',\n",
              " 'in',\n",
              " 'is',\n",
              " 'like',\n",
              " 'live',\n",
              " 'of',\n",
              " 'paris',\n",
              " 'professor',\n",
              " 'sally',\n",
              " 'sea',\n",
              " 'sells',\n",
              " 'shells',\n",
              " 'silly',\n",
              " 'stanford',\n",
              " 'strong',\n",
              " 'taiwan',\n",
              " 'the',\n",
              " 'to',\n",
              " 'today',\n",
              " 'turkey',\n",
              " 'we',\n",
              " 'wind'}"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZJwl7NkZqgmd"
      },
      "source": [
        "Convolutions allow our model to consider the surrounding `+N` or `-N` words of each word when making a prediction. In our earlier example `We always come to Paris` for `Paris`, if we have a window size of 1, that means our model will look at the words that come immediately before and after `Paris`, which are `to`, and, well, nothing. Now, this raises another issue. `Paris` is at the end of our sentence, so there isn't another word following it. Remember that we define the input dimensions of our `PyTorch` models when we are initializing them. If we set the window size to be `1`, it means that our model will be accepting `3` words in every pass. We cannot have our model expect `2` words from time to time.\n",
        "\n",
        "The solution is to introduce a special token, such as `<pad>`, that will be added to our sentences to make sure that every word has a valid window around them. Similar to `<unk>` token, we could pick another string for our pad token if we wanted, as long as we make sure it is used for a unique purpose."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "IgT4NGvy5rRx"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "10aoeAnLqgmd",
        "outputId": "85560f19-ab1d-4216-a9dd-09db7601892b"
      },
      "source": [
        "# Add the <pad> token to our vocabulary\n",
        "vocabulary.add(\"<pad>\")\n",
        "\n",
        "# Function that pads the given sentence\n",
        "# We are introducing this function here as an example\n",
        "# We will be utilizing it later in the tutorial\n",
        "def pad_window(sentence, window_size, pad_token=\"<pad>\"):\n",
        "  window = [pad_token] * window_size\n",
        "  return window + sentence + window\n",
        "\n",
        "# Show padding example\n",
        "window_size = 2\n",
        "pad_window(train_sentences[0], window_size=window_size)"
      ],
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['<pad>', '<pad>', 'we', 'always', 'come', 'to', 'paris', '<pad>', '<pad>']"
            ]
          },
          "metadata": {},
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gf8psr2gqgme"
      },
      "source": [
        "Now that our vocabularly is ready, let's assign an index to each of our words."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xLrnGLutqgme",
        "outputId": "abb925a8-2f4d-4257-9617-67134b165b65"
      },
      "source": [
        "# We are just converting our vocabularly to a list to be able to index into it\n",
        "# Sorting is not necessary, we sort to show an ordered word_to_ind dictionary\n",
        "# That being said, we will see that having the index for the padding token\n",
        "# be 0 is convenient as some PyTorch functions use it as a default value\n",
        "# such as nn.utils.rnn.pad_sequence, which we will cover in a bit\n",
        "ix_to_word = sorted(list(vocabulary))\n",
        "\n",
        "# Creating a dictionary to find the index of a given word\n",
        "word_to_ix = {word: ind for ind, word in enumerate(ix_to_word)}\n",
        "word_to_ix"
      ],
      "execution_count": 151,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'<pad>': 0,\n",
              " '<unk>': 1,\n",
              " 'always': 2,\n",
              " 'ankara': 3,\n",
              " 'australia': 4,\n",
              " 'capital': 5,\n",
              " 'come': 6,\n",
              " 'comes': 7,\n",
              " 'from': 8,\n",
              " 'he': 9,\n",
              " 'i': 10,\n",
              " 'icecream': 11,\n",
              " 'in': 12,\n",
              " 'is': 13,\n",
              " 'like': 14,\n",
              " 'live': 15,\n",
              " 'of': 16,\n",
              " 'paris': 17,\n",
              " 'professor': 18,\n",
              " 'sally': 19,\n",
              " 'sea': 20,\n",
              " 'sells': 21,\n",
              " 'shells': 22,\n",
              " 'silly': 23,\n",
              " 'stanford': 24,\n",
              " 'strong': 25,\n",
              " 'taiwan': 26,\n",
              " 'the': 27,\n",
              " 'to': 28,\n",
              " 'today': 29,\n",
              " 'turkey': 30,\n",
              " 'we': 31,\n",
              " 'wind': 32}"
            ]
          },
          "metadata": {},
          "execution_count": 151
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "LUCvtehrqgme",
        "outputId": "87053b0f-e760-447d-c807-88f19be68635"
      },
      "source": [
        "ix_to_word[1]"
      ],
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'<unk>'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n5PsSkwSqgme"
      },
      "source": [
        "Great! We are ready to convert our training sentences into a sequence of indices corresponding to each token."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "00S_m_2Hqgme",
        "outputId": "3332ba26-16c5-4995-e744-9e31c2fd5076"
      },
      "source": [
        "# Given a sentence of tokens, return the corresponding indices\n",
        "def convert_token_to_indices(sentence, word_to_ix):\n",
        "  indices = []\n",
        "  for token in sentence:\n",
        "    # Check if the token is in our vocabularly. If it is, get it's index.\n",
        "    # If not, get the index for the unknown token.\n",
        "    if token in word_to_ix:\n",
        "      index = word_to_ix[token]\n",
        "    else:\n",
        "      index = word_to_ix[\"<unk>\"]\n",
        "    indices.append(index)\n",
        "  return indices\n",
        "\n",
        "# More compact version of the same function\n",
        "def _convert_token_to_indices(sentence, word_to_ix):\n",
        "  return [word_to_ind.get(token, word_to_ix[\"<unk>\"]) for token in sentence]\n",
        "\n",
        "# Show an example\n",
        "example_sentence = [\"we\", \"always\", \"come\", \"to\", \"kuwait\"]\n",
        "example_indices = convert_token_to_indices(example_sentence, word_to_ix)\n",
        "restored_example = [ix_to_word[ind] for ind in example_indices]\n",
        "\n",
        "print(f\"Original sentence is: {example_sentence}\")\n",
        "print(f\"Going from words to indices: {example_indices}\")\n",
        "print(f\"Going from indices to words: {restored_example}\")"
      ],
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Original sentence is: ['we', 'always', 'come', 'to', 'kuwait']\n",
            "Going from words to indices: [31, 2, 6, 28, 1]\n",
            "Going from indices to words: ['we', 'always', 'come', 'to', '<unk>']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UrISNS1Iqgme"
      },
      "source": [
        "In the example above, `kuwait` shows up as `<unk>`, because it is not included in our vocabulary. Let's convert our `train_sentences` to `example_padded_indices`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pz1hNNmCqgme",
        "outputId": "5a14744a-6920-432a-9109-155dc145f282"
      },
      "source": [
        "# Converting our sentences to indices\n",
        "example_padded_indices = [convert_token_to_indices(s, word_to_ix) for s in train_sentences]\n",
        "example_padded_indices"
      ],
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[[31, 2, 6, 28, 17],\n",
              " [27, 18, 13, 8, 4],\n",
              " [10, 15, 12, 24],\n",
              " [9, 7, 8, 26],\n",
              " [27, 5, 16, 30, 13, 3],\n",
              " [10, 14, 11],\n",
              " [27, 32, 13, 25, 29],\n",
              " [23, 19, 21, 20, 22]]"
            ]
          },
          "metadata": {},
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sa3OVinUqgmf"
      },
      "source": [
        "Now that we have an index for each word in our vocabularly, we can create an embedding table with `nn.Embedding` class in `PyTorch`. It is called as follows `nn.Embedding(num_words, embedding_dimension)` where `num_words` is the number of words in our vocabulary and the `embedding_dimension` is the dimension of the embeddings we want to have. There is nothing fancy about `nn.Embedding`: it is just a wrapper class around a trainabe `NxE` dimensional tensor, where `N` is the number of words in our vocabulary and `E` is the number of embedding dimensions. This table is initially random, but it will change over time. As we train our network, the gradients will be backpropagated all the way to the embedding layer, and hence our word embeddings would be updated. We will initiliaze the embedding layer we will use for our model in our model, but we are showing an example here."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GlgK-9rwqgmf",
        "outputId": "b5c591d0-64fa-4242-b1ce-f2f84083c43c"
      },
      "source": [
        "# Creating an embedding table for our words\n",
        "embedding_dim = 5\n",
        "embeds = nn.Embedding(len(vocabulary), embedding_dim)\n",
        "\n",
        "# Printing the parameters in our embedding table\n",
        "list(embeds.parameters())"
      ],
      "execution_count": 155,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Parameter containing:\n",
              " tensor([[-0.2508, -0.1772,  2.6217, -0.8953,  1.1443],\n",
              "         [ 1.2067, -0.1719, -1.4160,  0.4550,  0.7160],\n",
              "         [-0.7000,  0.8746,  1.1649,  0.4060, -0.4833],\n",
              "         [ 0.5984, -0.7218,  0.3162, -0.5874, -1.0450],\n",
              "         [-0.8697,  0.9644, -0.6342,  1.1092, -0.1267],\n",
              "         [-0.4208, -0.0486,  0.0519,  0.9574, -1.0691],\n",
              "         [-0.6810, -0.1191, -0.4996,  0.2803,  1.4469],\n",
              "         [-1.8849, -1.7417,  0.5186,  0.3454,  0.1245],\n",
              "         [-0.4410, -0.5293,  1.5665,  1.7240, -1.6445],\n",
              "         [ 1.3117,  0.3496,  0.6352, -0.4387, -0.2778],\n",
              "         [-0.4991, -1.7354, -0.6294, -0.3289,  0.7460],\n",
              "         [ 1.7486,  0.3757, -0.9376,  1.5695, -0.3810],\n",
              "         [ 1.3277, -0.9387, -1.1757,  2.6685,  1.0423],\n",
              "         [-0.8088, -1.1036, -0.7134, -0.6101, -2.1951],\n",
              "         [-0.1886, -0.6023,  0.2141,  1.0487,  0.3638],\n",
              "         [ 0.9941,  0.9979,  0.7624,  0.7014,  0.1407],\n",
              "         [-0.3390, -0.2196,  0.3532, -0.4144,  1.1204],\n",
              "         [-1.2461,  0.2714, -1.7379,  0.1085, -0.1061],\n",
              "         [ 0.6235,  0.2743, -0.2231, -0.4730, -0.8815],\n",
              "         [ 1.5693, -0.2004,  0.1193, -1.5834,  0.9266],\n",
              "         [-1.2182,  0.6793, -1.0319, -1.3961, -0.9249],\n",
              "         [-0.2236,  0.4861, -2.4918,  1.4336, -2.1230],\n",
              "         [-2.0029,  0.6877,  1.0122,  1.3400,  0.6260],\n",
              "         [ 0.9434, -1.7719, -0.2389, -1.0063,  2.0645],\n",
              "         [-0.3443,  0.2632, -0.4601, -0.2103, -0.0387],\n",
              "         [ 0.3370,  1.1519, -1.3242,  1.0930,  0.1024],\n",
              "         [ 0.0103, -0.3954, -0.6435,  0.6406, -0.2835],\n",
              "         [ 0.4814,  0.3402,  0.3230,  2.1328,  0.2750],\n",
              "         [-0.6515, -0.7439,  1.5988, -1.9500, -2.7006],\n",
              "         [-1.0294,  0.2232,  1.3722,  2.2273,  0.7599],\n",
              "         [-0.3239, -0.6253, -0.6242,  0.9841,  0.5342],\n",
              "         [-1.9986,  0.3248, -1.2842,  0.4613,  0.4889],\n",
              "         [ 0.1624,  1.7379, -0.2858,  0.1501, -2.2698]], requires_grad=True)]"
            ]
          },
          "metadata": {},
          "execution_count": 155
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Blf6RtKqgmf"
      },
      "source": [
        "To get the word embedding for a word in our vocabulary, all we need to do is to create a lookup tensor. The lookup tensor is just a tensor containing the index we want to look up `nn.Embedding` class expects an index tensor that is of type Long Tensor, so we should create our tensor accordingly."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NQnTRfiOqgmf",
        "outputId": "410a2431-fafa-4471-a269-750ce40c086c"
      },
      "source": [
        "# Get the embedding for the word Paris\n",
        "index = word_to_ix[\"paris\"]\n",
        "index_tensor = torch.tensor(index, dtype=torch.long)\n",
        "print(f'{index_tensor=}')\n",
        "paris_embed = embeds(index_tensor)\n",
        "paris_embed"
      ],
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "index_tensor=tensor(17)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([-1.2461,  0.2714, -1.7379,  0.1085, -0.1061],\n",
              "       grad_fn=<EmbeddingBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 156
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ICGgONnnqgmf",
        "outputId": "c98f259f-1733-4eb6-c375-9833570e622d"
      },
      "source": [
        "# We can also get multiple embeddings at once\n",
        "index_paris = word_to_ix[\"paris\"]\n",
        "index_ankara = word_to_ix[\"ankara\"]\n",
        "indices = [index_paris, index_ankara]\n",
        "indices_tensor = torch.tensor(indices, dtype=torch.long)\n",
        "embeddings = embeds(indices_tensor)\n",
        "embeddings"
      ],
      "execution_count": 157,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[-1.2461,  0.2714, -1.7379,  0.1085, -0.1061],\n",
              "        [ 0.5984, -0.7218,  0.3162, -0.5874, -1.0450]],\n",
              "       grad_fn=<EmbeddingBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 157
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J_cWpnzPqgmf"
      },
      "source": [
        "Usually, we define the embedding layer as part of our model, which you will see in the later sections of our notebook."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e-ybR6bmqgmf"
      },
      "source": [
        "#### Batching Sentences\n",
        "\n",
        "Waiting our whole training corpus to be processed before making an update is costly. On the other hand, updating the parameters after every training example causes the loss to be less stable between updates. To combat these issues, we instead update our parameters after training on a batch of data. This allows us to get a better estimate of the gradient of the global loss. In this section, we will learn how to structure our data into batches using the `torch.util.data.DataLoader` class.\n",
        "\n",
        "We will be calling the `DataLoader` class as follows: `DataLoader(data, batch_size=batch_size, shuffle=True, collate_fn=collate_fn)`.  The `batch_size` parameter determines the number of examples per batch. In every epoch, we will be iterating over all the batches using the `DataLoader`. The order of batches is deterministic by default, but we can ask `DataLoader` to shuffle the batches by setting the `shuffle` parameter to `True`. This way we ensure that we don't encounter a bad batch multiple times.\n",
        "\n",
        "If provided, `DataLoader` passes the batches it prepares to the `collate_fn`. We can write a custom function to pass to the `collate_fn` parameter in order to print stats about our batch or perform extra processing. In our case, we will use the `collate_fn` to:\n",
        "1. Window pad our train sentences.\n",
        "2. Convert the words in the training examples to indices.\n",
        "3. Pad the training examples so that all the sentences have the same length.\n",
        "\n",
        "Because our version of the `collate_fn` function will need to access to our `word_to_ix` dictionary (so that it can turn words into indices), we will make use of the `partial` function in `Python`, which passes the parameters we give to the function we pass it."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "r_hH3Nfd5c36"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gu5KfaNUqgmf"
      },
      "source": [
        "from torch.utils.data import DataLoader\n",
        "from functools import partial\n",
        "\n",
        "def custom_collate_fn(batch, window_size, word_to_ix):\n",
        "  # Break our batch into the training examples (x) and labels (y)\n",
        "  # We are turning our x and y into tensors because nn.utils.rnn.pad_sequence\n",
        "  # method expects tensors. This is also useful since our model will be\n",
        "  # expecting tensor inputs.\n",
        "  x, y = zip(*batch)\n",
        "\n",
        "  # We will record the number of labels so that we know\n",
        "  # how many words existed in each example.\n",
        "  lengths = [len(words) for words in x]\n",
        "  lenghts = torch.LongTensor(lengths)\n",
        "\n",
        "  # Now we need to window pad our training examples. We have already defined a\n",
        "  # function to handle window padding. We are including it here again so that\n",
        "  # everything is in one place.\n",
        "  def pad_window(sentence, window_size, pad_token=\"<pad>\"):\n",
        "    window = [pad_token] * window_size\n",
        "    return window + sentence + window\n",
        "\n",
        "  # Pad the train examples.\n",
        "  x = [pad_window(s, window_size=window_size) for s in x]\n",
        "\n",
        "  # Now we need to turn words in our training examples to indices. We are\n",
        "  # copying the function defined earlier for the same reason as above.\n",
        "  def convert_tokens_to_indices(sentence, word_to_ix):\n",
        "    return [word_to_ix.get(token, word_to_ix[\"<unk>\"]) for token in sentence]\n",
        "\n",
        "  # Convert the train examples into indices.\n",
        "  x = [convert_tokens_to_indices(s, word_to_ix) for s in x]\n",
        "\n",
        "  # We will now pad the examples so that the lengths of all the example in\n",
        "  # one batch are the same, making it possible to do matrix operations.\n",
        "  # We set the batch_first parameter to True so that the returned matrix has\n",
        "  # the batch as the first dimension.\n",
        "  pad_token_ix = word_to_ix[\"<pad>\"]\n",
        "\n",
        "  # pad_sequence function expects the input to be a tensor, so we turn x into one\n",
        "  x = [torch.LongTensor(x_i) for x_i in x]\n",
        "  x_padded = nn.utils.rnn.pad_sequence(x, batch_first=True, padding_value=pad_token_ix)\n",
        "\n",
        "  y = torch.LongTensor(y)\n",
        "\n",
        "  # We are now ready to return our variables. The order we return our variables\n",
        "  # here will match the order we read them in our training loop.\n",
        "  return x_padded, y, lenghts"
      ],
      "execution_count": 158,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v0cSfZQMqgmg"
      },
      "source": [
        "This function seems long, but it really doesn't have to be. Check out the alternative version below where we remove the extra function declarations and comments."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BvHop7ilqgmg"
      },
      "source": [
        "def _custom_collate_fn(batch, window_size, word_to_ix):\n",
        "  # Prepare the datapoints\n",
        "  x, y = zip(*batch)\n",
        "  lengths = [len(words) for words in x]\n",
        "  lenghts = torch.LongTensor(lengths)\n",
        "  x = [pad_window(s, window_size=window_size) for s in x]\n",
        "  x = [convert_tokens_to_indices(s, word_to_ix) for s in x]\n",
        "\n",
        "  # Pad x so that all the examples in the batch have the same size\n",
        "  pad_token_ix = word_to_ix[\"<pad>\"]\n",
        "  x = [torch.LongTensor(x_i) for x_i in x]\n",
        "  x_padded = nn.utils.rnn.pad_sequence(x, batch_first=True, padding_value=pad_token_ix)\n",
        "\n",
        "  # Pad y and record the length\n",
        "  lengths = [len(label) for label in y]\n",
        "  lenghts = torch.LongTensor(lengths)\n",
        "  y = torch.LongTensor(y)\n",
        "\n",
        "  return x_padded, y, lenghts"
      ],
      "execution_count": 159,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e4pOkEsMqgmg"
      },
      "source": [
        "Now, we can see the `DataLoader` in action."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cd_xorbmqgmg",
        "outputId": "d333239f-aa3c-4432-a064-f8583d8356ae"
      },
      "source": [
        "# Parameters to be passed to the DataLoader\n",
        "data = list(zip(train_sentences, train_labels))\n",
        "batch_size = 2\n",
        "shuffle = True\n",
        "window_size = 2\n",
        "collate_fn = partial(custom_collate_fn, window_size=window_size, word_to_ix=word_to_ix)\n",
        "\n",
        "# Instantiate the DataLoader\n",
        "loader = DataLoader(data, batch_size=batch_size, shuffle=shuffle, collate_fn=collate_fn)\n",
        "\n",
        "# Go through one loop\n",
        "counter = 0\n",
        "for batched_x, batched_y, batched_lengths in loader:\n",
        "  print(f\"Iteration {counter}\")\n",
        "  print(\"Batched Input:\")\n",
        "  print(batched_x)\n",
        "  print(\"Batched Labels:\")\n",
        "  print(batched_y)\n",
        "  print(\"Batched Lengths:\")\n",
        "  print(batched_lengths)\n",
        "  print(\"\")\n",
        "  counter += 1"
      ],
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Iteration 0\n",
            "Batched Input:\n",
            "tensor([[ 0,  0, 27,  5, 16, 30, 13,  3,  0,  0],\n",
            "        [ 0,  0, 23, 19, 21, 20, 22,  0,  0,  0]])\n",
            "Batched Labels:\n",
            "tensor([1, 0])\n",
            "Batched Lengths:\n",
            "tensor([6, 5])\n",
            "\n",
            "Iteration 1\n",
            "Batched Input:\n",
            "tensor([[ 0,  0, 10, 15, 12, 24,  0,  0],\n",
            "        [ 0,  0, 10, 14, 11,  0,  0,  0]])\n",
            "Batched Labels:\n",
            "tensor([1, 0])\n",
            "Batched Lengths:\n",
            "tensor([4, 3])\n",
            "\n",
            "Iteration 2\n",
            "Batched Input:\n",
            "tensor([[ 0,  0,  9,  7,  8, 26,  0,  0,  0],\n",
            "        [ 0,  0, 31,  2,  6, 28, 17,  0,  0]])\n",
            "Batched Labels:\n",
            "tensor([1, 1])\n",
            "Batched Lengths:\n",
            "tensor([4, 5])\n",
            "\n",
            "Iteration 3\n",
            "Batched Input:\n",
            "tensor([[ 0,  0, 27, 32, 13, 25, 29,  0,  0],\n",
            "        [ 0,  0, 27, 18, 13,  8,  4,  0,  0]])\n",
            "Batched Labels:\n",
            "tensor([0, 1])\n",
            "Batched Lengths:\n",
            "tensor([5, 5])\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RzrTSp0eqgmg"
      },
      "source": [
        "The batched input tensors you see above will be passed into our model. On the other hand, we started off saying that our model will be a window classifier. The way our input tensors are currently formatted, we have all the words in a sentence in one datapoint. When we pass this input to our model, it needs to create the windows for each word.\n",
        "\n",
        "We could avoid this problem if we formatted our data by breaking it into windows beforehand. In this example, we will instead how our model take care of the formatting.\n",
        "\n",
        "Given that our `window_size` is `N` we want our model to make a prediction on every `2N+1` tokens. That is, if we have an input with `9` tokens, and a `window_size` of `2`, we want our model to return `5` predictions. This makes sense because before we padded it with `2` tokens on each side, our input also had `5` tokens in it!\n",
        "\n",
        "We can create these windows by using for loops, but there is a faster `PyTorch` alternative, which is the `unfold(dimension, size, step)` method. We can create the windows we need using this method as follows:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t0okHsvnqgmg",
        "outputId": "cfea5b19-cf34-467d-8b39-65b767711bb7"
      },
      "source": [
        "# Print the original tensor\n",
        "print(f\"Original Tensor: \")\n",
        "print(batched_x)\n",
        "print(\"\")\n",
        "\n",
        "# Create the 2 * 2 + 1 chunks\n",
        "chunk = batched_x.unfold(1, window_size*2 + 1, 1)\n",
        "print(f\"Windows: \")\n",
        "print(chunk)"
      ],
      "execution_count": 161,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Original Tensor: \n",
            "tensor([[ 0,  0, 27, 32, 13, 25, 29,  0,  0],\n",
            "        [ 0,  0, 27, 18, 13,  8,  4,  0,  0]])\n",
            "\n",
            "Windows: \n",
            "tensor([[[ 0,  0, 27, 32, 13],\n",
            "         [ 0, 27, 32, 13, 25],\n",
            "         [27, 32, 13, 25, 29],\n",
            "         [32, 13, 25, 29,  0],\n",
            "         [13, 25, 29,  0,  0]],\n",
            "\n",
            "        [[ 0,  0, 27, 18, 13],\n",
            "         [ 0, 27, 18, 13,  8],\n",
            "         [27, 18, 13,  8,  4],\n",
            "         [18, 13,  8,  4,  0],\n",
            "         [13,  8,  4,  0,  0]]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YPDT0Rsyqgmg"
      },
      "source": [
        "### Model\n",
        "\n",
        "Now that we have prepared our data, we are ready to build our model. We have learned how to write custom `nn.Module` classes. We will do the same here and put everything we have learned so far together."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uE0DVnQmqgmh"
      },
      "source": [
        "class SentenceClassifier(nn.Module):\n",
        "\n",
        "  def __init__(self, hyperparameters, vocab_size, pad_ix=0, embeds=None):\n",
        "    super().__init__()\n",
        "\n",
        "    \"\"\" Instance variables \"\"\"\n",
        "    self.window_size = hyperparameters[\"window_size\"]\n",
        "    self.embed_dim = hyperparameters[\"embed_dim\"]\n",
        "    self.hidden_dim = hyperparameters[\"hidden_dim\"]\n",
        "    self.freeze_embeddings = hyperparameters[\"freeze_embeddings\"]\n",
        "\n",
        "    \"\"\" Embedding Layer\n",
        "    Takes in a tensor containing embedding indices, and returns the\n",
        "    corresponding embeddings. The output is of dim\n",
        "    (number_of_indices * embedding_dim).\n",
        "\n",
        "    If freeze_embeddings is True, set the embedding layer parameters to be\n",
        "    non-trainable. This is useful if we only want the parameters other than the\n",
        "    embeddings parameters to change.\n",
        "\n",
        "    \"\"\"\n",
        "    if embeds is None:\n",
        "        self.embeds = nn.Embedding(vocab_size, self.embed_dim, padding_idx=pad_ix)\n",
        "    else:\n",
        "        self.embeds = nn.Embedding.from_pretrained(embeds, freeze=self.freeze_embeddings, padding_idx=pad_ix)\n",
        "    if self.freeze_embeddings:\n",
        "      self.embed_layer.weight.requires_grad = False\n",
        "\n",
        "    \"\"\" Hidden Layers\n",
        "    \"\"\"\n",
        "    full_window_size = 2 * window_size + 1\n",
        "    self.hidden_layer = nn.Sequential(\n",
        "      nn.Linear(full_window_size * self.embed_dim, self.hidden_dim),\n",
        "      nn.ReLU()\n",
        "    )\n",
        "\n",
        "    self.globalpooling = partial(torch.mean, dim=1)\n",
        "\n",
        "    \"\"\" Output Layer\n",
        "    \"\"\"\n",
        "    self.output_layer = nn.Linear(self.hidden_dim, 1)\n",
        "\n",
        "    \"\"\" Probabilities\n",
        "    \"\"\"\n",
        "    self.probabilities = nn.Sigmoid()\n",
        "\n",
        "  def forward(self, inputs):\n",
        "    \"\"\"\n",
        "    Let B:= batch_size\n",
        "        L:= window-padded sentence length\n",
        "        D:= self.embed_dim\n",
        "        S:= self.window_size\n",
        "        H:= self.hidden_dim\n",
        "\n",
        "    inputs: a (B, L) tensor of token indices\n",
        "    \"\"\"\n",
        "    B, L = inputs.size()\n",
        "\n",
        "    \"\"\"\n",
        "    Reshaping.\n",
        "    Takes in a (B, L) LongTensor\n",
        "    Outputs a (B, L~, S) LongTensor\n",
        "    \"\"\"\n",
        "    # Fist, get our word windows for each word in our input.\n",
        "    token_windows = inputs.unfold(1, 2 * self.window_size + 1, 1)\n",
        "    _, adjusted_length, _ = token_windows.size()\n",
        "\n",
        "    # Good idea to do internal tensor-size sanity checks, at the least in comments!\n",
        "    assert token_windows.size() == (B, adjusted_length, 2 * self.window_size + 1)\n",
        "\n",
        "    \"\"\"\n",
        "    Embedding.\n",
        "    Takes in a torch.LongTensor of size (B, L~, S)\n",
        "    Outputs a (B, L~, S, D) FloatTensor.\n",
        "    \"\"\"\n",
        "    embedded_windows = self.embeds(token_windows)\n",
        "\n",
        "    \"\"\"\n",
        "    Reshaping.\n",
        "    Takes in a (B, L~, S, D) FloatTensor.\n",
        "    Resizes it into a (B, L~, S*D) FloatTensor.\n",
        "    -1 argument \"infers\" what the last dimension should be based on leftover axes.\n",
        "    \"\"\"\n",
        "    embedded_windows = embedded_windows.view(B, adjusted_length, -1)\n",
        "\n",
        "    \"\"\"\n",
        "    Layer 1.\n",
        "    Takes in a (B, L~, S*D) FloatTensor.\n",
        "    Resizes it into a (B, L~, H) FloatTensor\n",
        "    \"\"\"\n",
        "    layer_1 = self.hidden_layer(embedded_windows)\n",
        "\n",
        "    \"\"\"\n",
        "    Layer 2\n",
        "    Takes in a (B, L~, H) FloatTensor\n",
        "    Resizes it into a (B, H)\n",
        "    \"\"\"\n",
        "    layer_2 = self.globalpooling(layer_1)\n",
        "\n",
        "    \"\"\"\n",
        "    Layer 3\n",
        "    Takes in a (B, H) FloatTensor.\n",
        "    Resizes it into a (B, 1) FloatTensor.\n",
        "    \"\"\"\n",
        "    output = self.output_layer(layer_2)\n",
        "\n",
        "    \"\"\"\n",
        "    Softmax.\n",
        "    Takes in a (B, 1) FloatTensor of unnormalized class scores.\n",
        "    Outputs a (B) FloatTensor of (log-)normalized class scores.\n",
        "    \"\"\"\n",
        "    output = self.probabilities(output)\n",
        "    output = output.view(B)\n",
        "\n",
        "    return output"
      ],
      "execution_count": 162,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W1kxsoVXqgmh"
      },
      "source": [
        "### Training\n",
        "\n",
        "We are now ready to put everything together. Let's start with preparing our data and intializing our model. We can then intialize our optimizer and define our loss function. This time, instead of using one of the predefined loss function as we did before, we will define our own loss function."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ebRnSGjlqgmh"
      },
      "source": [
        "# Prepare the data\n",
        "data = list(zip(train_sentences, train_labels))\n",
        "batch_size = 2\n",
        "shuffle = True\n",
        "window_size = 2\n",
        "collate_fn = partial(custom_collate_fn, window_size=window_size, word_to_ix=word_to_ix)\n",
        "\n",
        "# Instantiate a DataLoader\n",
        "loader = DataLoader(data, batch_size=batch_size, shuffle=shuffle, collate_fn=collate_fn)\n",
        "\n",
        "# Initialize a model\n",
        "# It is useful to put all the model hyperparameters in a dictionary\n",
        "model_hyperparameters = {\n",
        "    \"batch_size\": 4,\n",
        "    \"window_size\": 2,\n",
        "    \"embed_dim\": 25,\n",
        "    \"hidden_dim\": 25,\n",
        "    \"freeze_embeddings\": False,\n",
        "}\n",
        "\n",
        "vocab_size = len(word_to_ix)\n",
        "model = SentenceClassifier(model_hyperparameters, vocab_size)\n",
        "\n",
        "# Define an optimizer\n",
        "learning_rate = 0.01\n",
        "optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)\n",
        "\n",
        "# Define a loss function, which computes to binary cross entropy loss\n",
        "def loss_function(batch_outputs, batch_labels, batch_lengths):\n",
        "    # Calculate the loss for the whole batch\n",
        "    bceloss = nn.BCELoss()\n",
        "    loss = bceloss(batch_outputs, batch_labels.float())\n",
        "\n",
        "    # Rescale the loss. Remember that we have used lengths to store the\n",
        "    # number of words in each training example\n",
        "    loss = loss / batch_lengths.sum().float()\n",
        "\n",
        "    return loss"
      ],
      "execution_count": 163,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "svpPfyLyqgmh"
      },
      "source": [
        "Unlike our earlier example, this time instead of passing all of our training data to the model at once in each epoch, we will be utilizing batches. Hence, in each training epoch iteration, we also iterate over the batches."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SrodgxgKqgmh"
      },
      "source": [
        "# Function that will be called in every epoch\n",
        "def train_epoch(loss_function, optimizer, model, loader):\n",
        "\n",
        "  # Keep track of the total loss for the batch\n",
        "  total_loss = 0\n",
        "  for batch_inputs, batch_labels, batch_lengths in loader:\n",
        "    # Clear the gradients\n",
        "    optimizer.zero_grad()\n",
        "    # Run a forward pass\n",
        "    outputs = model.forward(batch_inputs)\n",
        "    # Compute the batch loss\n",
        "    loss = loss_function(outputs, batch_labels, batch_lengths)\n",
        "    # Calculate the gradients\n",
        "    loss.backward()\n",
        "    # Update the parameteres\n",
        "    optimizer.step()\n",
        "    total_loss += loss.item()\n",
        "\n",
        "  return total_loss\n",
        "\n",
        "\n",
        "# Function containing our main training loop\n",
        "def train(loss_function, optimizer, model, loader, num_epochs=10000):\n",
        "\n",
        "  # Iterate through each epoch and call our train_epoch function\n",
        "  for epoch in range(num_epochs):\n",
        "    epoch_loss = train_epoch(loss_function, optimizer, model, loader)\n",
        "    if epoch % 100 == 0: print(epoch_loss)"
      ],
      "execution_count": 164,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uzU-s1pzqgmh"
      },
      "source": [
        "Let's start training!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aM0sC_fkqgmi",
        "outputId": "6d1c6b4e-a945-4828-d622-2f1715b60d67"
      },
      "source": [
        "num_epochs = 500\n",
        "train(loss_function, optimizer, model, loader, num_epochs=num_epochs)"
      ],
      "execution_count": 165,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.3029877506196499\n",
            "0.27535929158329964\n",
            "0.25787004083395004\n",
            "0.24039870128035545\n",
            "0.22824683412909508\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GkAIryu7qgmi"
      },
      "source": [
        "### Prediction\n",
        "\n",
        "Let's see how well our model is at making predictions. We can start by creating our test data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oJGJ8UE8qgmi"
      },
      "source": [
        "# Create test sentences\n",
        "test_corpus = [\"She comes from Paris\", \"I like wind\", \"She comes Paris\", \"She comes to Paris\", \"She comes from Moscow to Tver\"]\n",
        "test_sentences = [s.lower().split() for s in test_corpus]\n",
        "test_labels = [1, 0, 1, 1, 1]\n",
        "\n",
        "# Create a test loader\n",
        "test_data = list(zip(test_sentences, test_labels))\n",
        "batch_size = 1\n",
        "shuffle = False\n",
        "window_size = 2\n",
        "collate_fn = partial(custom_collate_fn, window_size=2, word_to_ix=word_to_ix)\n",
        "test_loader = torch.utils.data.DataLoader(test_data,\n",
        "                                           batch_size=1,\n",
        "                                           shuffle=False,\n",
        "                                           collate_fn=collate_fn)"
      ],
      "execution_count": 166,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YlJFQG0kqgmi"
      },
      "source": [
        "Let's loop over our test examples to see how well we are doing."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e8lYkc6Sqgmi",
        "outputId": "d8efea78-0eac-49ca-d701-79db71fa3ca4"
      },
      "source": [
        "for (test_instance, labels, _), text in zip(test_loader, test_corpus):\n",
        "  outputs = model.forward(test_instance)\n",
        "  print(labels)\n",
        "  print(text)\n",
        "  print(outputs)\n",
        "  print()"
      ],
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([1])\n",
            "She comes from Paris\n",
            "tensor([0.6772], grad_fn=<ViewBackward0>)\n",
            "\n",
            "tensor([0])\n",
            "I like wind\n",
            "tensor([0.4377], grad_fn=<ViewBackward0>)\n",
            "\n",
            "tensor([1])\n",
            "She comes Paris\n",
            "tensor([0.5806], grad_fn=<ViewBackward0>)\n",
            "\n",
            "tensor([1])\n",
            "She comes to Paris\n",
            "tensor([0.6673], grad_fn=<ViewBackward0>)\n",
            "\n",
            "tensor([1])\n",
            "She comes from Moscow to Tver\n",
            "tensor([0.7414], grad_fn=<ViewBackward0>)\n",
            "\n"
          ]
        }
      ]
    }
  ]
}