notebooks/CLIP_GPT_COCO.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jWoiEoWBAlXO"
      },
      "source": [
        "# CLIP-GPT\n",
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_6w5Qjgx3dmG"
      },
      "source": [
        "### Setup Environment"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "srzTbkHL3cyX",
        "outputId": "61f039a5-c551-48ec-f9f6-3d2dca3fa80d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.27.1-py3-none-any.whl (6.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.7/6.7 MB\u001b[0m \u001b[31m17.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.9/dist-packages (from transformers) (6.0)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.9/dist-packages (from transformers) (1.22.4)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.9/dist-packages (from transformers) (4.65.0)\n",
            "Collecting huggingface-hub<1.0,>=0.11.0\n",
            "  Downloading huggingface_hub-0.13.2-py3-none-any.whl (199 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.2/199.2 KB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from transformers) (23.0)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.9/dist-packages (from transformers) (2022.10.31)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from transformers) (2.27.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from transformers) (3.10.0)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m11.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.5.0)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (2.0.12)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (2022.12.7)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (3.4)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->transformers) (1.26.15)\n",
            "Installing collected packages: tokenizers, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.13.2 tokenizers-0.13.2 transformers-4.27.1\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting git+https://github.com/openai/CLIP.git\n",
            "  Cloning https://github.com/openai/CLIP.git to /tmp/pip-req-build-x_gb44ku\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/openai/CLIP.git /tmp/pip-req-build-x_gb44ku\n",
            "  Resolved https://github.com/openai/CLIP.git to commit a9b1bf5920416aaeaec965c25dd9e8f98c864f16\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting ftfy\n",
            "  Downloading ftfy-6.1.1-py3-none-any.whl (53 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m53.1/53.1 KB\u001b[0m \u001b[31m2.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: regex in /usr/local/lib/python3.9/dist-packages (from clip==1.0) (2022.10.31)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.9/dist-packages (from clip==1.0) (4.65.0)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.9/dist-packages (from clip==1.0) (1.13.1+cu116)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.9/dist-packages (from clip==1.0) (0.14.1+cu116)\n",
            "Requirement already satisfied: wcwidth>=0.2.5 in /usr/local/lib/python3.9/dist-packages (from ftfy->clip==1.0) (0.2.6)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.9/dist-packages (from torch->clip==1.0) (4.5.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from torchvision->clip==1.0) (1.22.4)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.9/dist-packages (from torchvision->clip==1.0) (8.4.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from torchvision->clip==1.0) (2.27.1)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->torchvision->clip==1.0) (1.26.15)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->torchvision->clip==1.0) (2.0.12)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->torchvision->clip==1.0) (2022.12.7)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->torchvision->clip==1.0) (3.4)\n",
            "Building wheels for collected packages: clip\n",
            "  Building wheel for clip (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for clip: filename=clip-1.0-py3-none-any.whl size=1369398 sha256=28243fa007ce947834f7af24625767601ad59d66688eb53467cf415210f7f9cd\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-5vwpmomk/wheels/c8/e4/e1/11374c111387672fc2068dfbe0d4b424cb9cdd1b2e184a71b5\n",
            "Successfully built clip\n",
            "Installing collected packages: ftfy, clip\n",
            "Successfully installed clip-1.0 ftfy-6.1.1\n"
          ]
        }
      ],
      "source": [
        "!pip install transformers\n",
        "!pip install git+https://github.com/openai/CLIP.git\n",
        "!pip install clip-retrieval"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "ZwGSyHbQ2qtV"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import requests\n",
        "import json\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "from torch.utils.data import Dataset, DataLoader\n",
        "from transformers import GPT2Tokenizer, GPT2LMHeadModel\n",
        "from transformers.optimization import get_linear_schedule_with_warmup\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from tqdm.notebook import tqdm\n",
        "import skimage.io as io\n",
        "import matplotlib.pyplot as plt\n",
        "from IPython.display import Image, display\n",
        "\n",
        "from pycocotools.coco import COCO\n",
        "from clip_retrieval.clip_client import ClipClient, Modality"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "u-i-K-D47K1I",
        "outputId": "98022510-fb67-4596-edd2-9d3a0de4364d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'cuda'"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "device"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "UdoYo2LX3GWk"
      },
      "source": [
        "### Fetch Data\n",
        "\n",
        "Likely want to store these for future reuse.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_y4TM6Vs4Drg"
      },
      "source": [
        "MS-COCO 2017 Training Captions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ukpr9Xai3F0x",
        "outputId": "4bfdb18e-ce1f-4eae-e366-4c4861ec5429"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-03-19 22:16:30--  http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
            "Resolving images.cocodataset.org (images.cocodataset.org)... 54.231.172.137, 52.217.123.217, 54.231.197.153, ...\n",
            "Connecting to images.cocodataset.org (images.cocodataset.org)|54.231.172.137|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 252907541 (241M) [application/zip]\n",
            "Saving to: ‘annotations_trainval2017.zip’\n",
            "\n",
            "annotations_trainva 100%[===================>] 241.19M  13.2MB/s    in 20s     \n",
            "\n",
            "2023-03-19 22:16:51 (11.9 MB/s) - ‘annotations_trainval2017.zip’ saved [252907541/252907541]\n",
            "\n",
            "Archive:  /content/annotations_trainval2017.zip\n",
            "  inflating: annotations/instances_train2017.json  \n",
            "  inflating: annotations/instances_val2017.json  \n",
            "  inflating: annotations/captions_train2017.json  \n",
            "  inflating: annotations/captions_val2017.json  \n",
            "  inflating: annotations/person_keypoints_train2017.json  \n",
            "  inflating: annotations/person_keypoints_val2017.json  \n"
          ]
        }
      ],
      "source": [
        "!wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
        "!unzip /content/annotations_trainval2017.zip"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JVOEONLy4U3s"
      },
      "source": [
        "MS-COCO 2017 Training Images"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "or3-_NIW4X4c",
        "outputId": "9a7849bd-826c-4ed4-aee3-cb9d28326315"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            " extracting: train2017/000000267201.jpg  \n",
            " extracting: train2017/000000213204.jpg  \n",
            " extracting: train2017/000000157184.jpg  \n",
            " extracting: train2017/000000139739.jpg  \n",
            " extracting: train2017/000000224928.jpg  \n",
            " extracting: train2017/000000037336.jpg  \n",
            " extracting: train2017/000000178771.jpg  \n",
            " extracting: train2017/000000024577.jpg  \n",
            " extracting: train2017/000000256903.jpg  \n",
            " extracting: train2017/000000421882.jpg  \n",
            " extracting: train2017/000000318200.jpg  \n",
            " extracting: train2017/000000544691.jpg  \n",
            " extracting: train2017/000000325022.jpg  \n",
            " extracting: train2017/000000417478.jpg  \n",
            " extracting: train2017/000000000670.jpg  \n",
            " extracting: train2017/000000299115.jpg  \n",
            " extracting: train2017/000000138641.jpg  \n",
            " extracting: train2017/000000293825.jpg  \n",
            " extracting: train2017/000000483297.jpg  \n",
            " extracting: train2017/000000343821.jpg  \n",
            " extracting: train2017/000000523245.jpg  \n",
            " extracting: train2017/000000443360.jpg  \n",
            " extracting: train2017/000000005706.jpg  \n",
            " extracting: train2017/000000489983.jpg  \n",
            " extracting: train2017/000000206934.jpg  \n",
            " extracting: train2017/000000564481.jpg  \n"
          ]
        }
      ],
      "source": [
        "!wget http://images.cocodataset.org/zips/train2017.zip\n",
        "!unzip /content/train2017.zip"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9TkNZ4bu7ANV"
      },
      "source": [
        "### Create CLIP Embeddings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OyxpNnqX7GGs",
        "outputId": "25970fdb-6df3-493c-d56a-a0ae82e139c5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['RN50',\n",
              " 'RN101',\n",
              " 'RN50x4',\n",
              " 'RN50x16',\n",
              " 'RN50x64',\n",
              " 'ViT-B/32',\n",
              " 'ViT-B/16',\n",
              " 'ViT-L/14',\n",
              " 'ViT-L/14@336px']"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "clip.available_models()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iz5RxSyY7zA1",
        "outputId": "b8446705-b291-45a8-d37b-f212745f8ac1"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|████████████████████████████████████████| 890M/890M [00:04<00:00, 216MiB/s]\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "CLIP(\n",
              "  (visual): VisionTransformer(\n",
              "    (conv1): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)\n",
              "    (ln_pre): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "    (transformer): Transformer(\n",
              "      (resblocks): Sequential(\n",
              "        (0): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (1): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (2): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (3): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (4): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (5): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (6): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (7): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (8): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (9): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (10): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (11): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (12): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (13): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (14): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (15): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (16): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (17): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (18): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (19): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (20): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (21): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (22): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "        (23): ResidualAttentionBlock(\n",
              "          (attn): MultiheadAttention(\n",
              "            (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "          (mlp): Sequential(\n",
              "            (c_fc): Linear(in_features=1024, out_features=4096, bias=True)\n",
              "            (gelu): QuickGELU()\n",
              "            (c_proj): Linear(in_features=4096, out_features=1024, bias=True)\n",
              "          )\n",
              "          (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "        )\n",
              "      )\n",
              "    )\n",
              "    (ln_post): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)\n",
              "  )\n",
              "  (transformer): Transformer(\n",
              "    (resblocks): Sequential(\n",
              "      (0): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (1): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (2): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (3): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (4): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (5): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (6): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (7): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (8): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (9): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (10): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "      (11): ResidualAttentionBlock(\n",
              "        (attn): MultiheadAttention(\n",
              "          (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "        (mlp): Sequential(\n",
              "          (c_fc): Linear(in_features=768, out_features=3072, bias=True)\n",
              "          (gelu): QuickGELU()\n",
              "          (c_proj): Linear(in_features=3072, out_features=768, bias=True)\n",
              "        )\n",
              "        (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              "      )\n",
              "    )\n",
              "  )\n",
              "  (token_embedding): Embedding(49408, 768)\n",
              "  (ln_final): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
              ")"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%%capture\n",
        "clip_model, preprocess = clip.load(\"ViT-L/14\", device=device) # output dim of 768\n",
        "clip_model.to(device).eval()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "Glmpd7pm7d3J"
      },
      "outputs": [],
      "source": [
        "def batch_encode(image_dir, batch_size=64):\n",
        "    image_tensors = []\n",
        "\n",
        "    for i in tqdm(range(0, len(os.listdir(image_dir)), batch_size)):\n",
        "        images = []\n",
        "\n",
        "        with torch.no_grad():\n",
        "            for filename in os.listdir(image_dir)[i:i+batch_size]: \n",
        "                images.append(preprocess(Image.open(os.path.join(image_dir, filename))).unsqueeze(0))\n",
        "\n",
        "            image_tensors.append(clip_model.encode_image(torch.cat(images, dim=0).to(device)).detach().cpu())\n",
        "\n",
        "    np.save(f\"/content/coco_embs/coco_train2017_clip_ViT-L-14_embs.npy\", torch.cat(image_tensors, dim=0).numpy(), allow_pickle=True)\n",
        "    \n",
        "    return"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-Qs10sQQ7HsW"
      },
      "outputs": [],
      "source": [
        "batch_encode(image_dir=\"/content/train2017/\", batch_size=512)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "id": "7oGQT_n29D-z"
      },
      "outputs": [],
      "source": [
        "with torch.no_grad():\n",
        "    torch.cuda.empty_cache()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6mrlTMBq34cZ"
      },
      "source": [
        "### Load GPT-2 Tokenizer and Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "gDrce5372qtW"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "tokenizer = GPT2Tokenizer.from_pretrained('gpt2')\n",
        "tokenizer.pad_token = tokenizer.eos_token\n",
        "tokenizer.add_special_tokens({\"additional_special_tokens\": [\"[CLIP IN]\", \"[\\CLIP IN]\", \"[CLIP OUT]\", \"[\\CLIP OUT]\"]})\n",
        "\n",
        "model = GPT2LMHeadModel.from_pretrained('gpt2').to(device)\n",
        "model.resize_token_embeddings(len(tokenizer))\n",
        "model.eval()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GR-KhQx_2qtW"
      },
      "source": [
        "### Setup Data for Training"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CBYatXdt2qtX",
        "outputId": "797a4443-59c5-4561-c439-b94012a8a91f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "torch.Size([118287, 768])\n"
          ]
        }
      ],
      "source": [
        "coco_images = np.load(\"/content/coco_embs/coco_train2017_clip_ViT-L-14_embs.npy\")\n",
        "coco_images_tensor = torch.Tensor(coco_images)\n",
        "print(coco_images_tensor.size())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "rqSC0-NL2qtX"
      },
      "outputs": [],
      "source": [
        "class COCODataset(Dataset):\n",
        "    def __init__(self, caption_file, image_dir):\n",
        "        self.coco_captions = COCO(caption_file)\n",
        "\n",
        "        self.files = os.listdir(image_dir)\n",
        "        self.file_id_dict = {}\n",
        "        self.coco_data = []\n",
        "\n",
        "        # Create data tuples: (caption, image_id, CLIP embedding, index of embedding)\n",
        "        for i, f in enumerate(self.files):\n",
        "            file_id = int(f[:-4])\n",
        "            self.file_id_dict[i] = file_id\n",
        "            for ann_id in self.coco_captions.getAnnIds(imgIds=file_id):\n",
        "                if np.random.random() < 0.5:\n",
        "                    text = \"Caption: [\" + self.coco_captions.loadAnns(ids=ann_id)[0][\"caption\"].strip() + \"]. [CLIP OUT][\\CLIP OUT]\"\n",
        "                    clip_pos = -1\n",
        "                else:\n",
        "                    text = \"[CLIP IN] [\\CLIP IN] Caption: [\" + self.coco_captions.loadAnns(ids=ann_id)[0][\"caption\"].strip() + \"].\"\n",
        "                    clip_pos = 1\n",
        "\n",
        "                self.coco_data.append((text, \n",
        "                self.coco_captions.loadAnns(ids=ann_id)[0][\"image_id\"],\n",
        "                coco_images_tensor[i].unsqueeze(0),\n",
        "                clip_pos))\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.coco_data)\n",
        "\n",
        "    def __getitem__(self, idx):\n",
        "        return self.coco_data[idx]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qas3R2e42qtY",
        "outputId": "b182d8ae-b226-4477-8db5-3d179fbfa953"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "loading annotations into memory...\n",
            "Done (t=1.21s)\n",
            "creating index...\n",
            "index created!\n"
          ]
        }
      ],
      "source": [
        "coco_dataset = COCODataset(caption_file=\"/content/annotations/captions_train2017.json\", image_dir=\"/content/train2017/\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "fDagGWbC2qtY"
      },
      "outputs": [],
      "source": [
        "def collate_fn(batch):\n",
        "    captions, img_ids, clip_embs, clip_pos = [], [], [], []\n",
        "    for cap, im_id, emb, p in batch:\n",
        "        captions.append(cap)\n",
        "        img_ids.append(im_id)\n",
        "        clip_embs.append(emb)\n",
        "        clip_pos.append(p)\n",
        "    \n",
        "    clip_embs = torch.cat(clip_embs, dim=0)\n",
        "    \n",
        "    return captions, img_ids, clip_embs, clip_pos"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V-iQzlMe2qtY"
      },
      "source": [
        "sample"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "IjWlmAMQ2qtY",
        "outputId": "3b71b35b-9aee-418a-abc6-c9892a1818b4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "('[CLIP IN] [\\\\CLIP IN] Caption: [A United airliner traveling down the run way.].', 41808)\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "sample_id = 2547\n",
        "print(coco_dataset.coco_data[sample_id][:2])\n",
        "I = io.imread(coco_dataset.coco_captions.loadImgs(coco_dataset.coco_data[sample_id][1])[0]['coco_url'])\n",
        "plt.axis('off')\n",
        "plt.imshow(I)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6uOMeXCT2qtY"
      },
      "source": [
        "### Tune GPT to predict CLIP embeddings from image captions as a continuous output"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "re4VtXHs2qtY"
      },
      "outputs": [],
      "source": [
        "def train_lm(model, tokenizer, caps, embs, clip_pos):\n",
        "    # TODO: Optimize training\n",
        "    \n",
        "    criterion_ce = torch.nn.CrossEntropyLoss()\n",
        "    criterion_mse = torch.nn.MSELoss()\n",
        "\n",
        "    targets = tokenizer(caps, padding=True, return_tensors='pt', return_attention_mask=True)\n",
        "    targets_ids = targets['input_ids'].to(device)\n",
        "    targets_mask = targets['attention_mask'].to(device)\n",
        "\n",
        "    token_embs = model.transformer.wte(targets_ids)\n",
        "\n",
        "    # Create placeholder tensors to concatenate CLIP embeddings in the case of CLIP->caption\n",
        "    input_clip_embs = torch.zeros((token_embs.size(0), token_embs.size(1)+1, token_embs.size(2)), device=device)\n",
        "    target_clip_mask = torch.zeros((targets_mask.size(0), targets_mask.size(1)+1), dtype=torch.int64, device=device)\n",
        "    target_clip_ids = torch.zeros((targets_ids.size(0), targets_ids.size(1)+1), dtype=torch.int64, device=device)\n",
        "\n",
        "    embedding_ids = []  # Store indices of caption->CLIP examples\n",
        "    captioning_ids = [] # Store indices of CLIP->caption examples\n",
        "    for c in range(len(caps)):\n",
        "        if clip_pos[c] < 0:\n",
        "            embedding_ids.append(c)\n",
        "\n",
        "            tok_count = torch.sum(targets_mask[c])\n",
        "            pos = tok_count - abs(clip_pos[c])     # position of [\\CLIP OUT] token, while ignoring variable padding \n",
        "\n",
        "            target_clip_ids[c] = torch.cat((targets_ids[c, :pos+1], torch.full((1,), fill_value=13).to(device), targets_ids[c, pos+1:]), dim=0) # Add period token to match placeholder tensor size\n",
        "            target_clip_mask[c, :tok_count+1] = 1\n",
        "\n",
        "            with torch.no_grad():\n",
        "                input_clip_embs[c] = torch.cat((token_embs[c, :pos+1], model.transformer.wte(torch.tensor([13]).to(device)).reshape(1, -1), token_embs[c, pos+1:]), dim=0)\n",
        "                \n",
        "        else:\n",
        "            captioning_ids.append(c)\n",
        "            pos = clip_pos[c]        # position of [\\CLIP IN] token\n",
        "\n",
        "            input_clip_embs[c] = torch.cat((token_embs[c, :pos], embs[c].reshape(1, -1).to(device), token_embs[c, pos:]), dim=0) # Add input CLIP embedding\n",
        "            target_clip_ids[c] = torch.cat((targets_ids[c, :pos], torch.zeros((1,)).to(device), targets_ids[c, pos:]), dim=0)    # Add dummy token; is ignored in loss \n",
        "            target_clip_mask[c] = torch.cat((targets_mask[c, :pos], torch.ones((1,)).to(device), targets_mask[c, pos:]), dim=0)  # Avoid masking new token\n",
        "\n",
        "    outputs = model(\n",
        "        inputs_embeds=input_clip_embs,\n",
        "        return_dict=True,\n",
        "        output_hidden_states=True,\n",
        "        attention_mask=target_clip_mask\n",
        "    )\n",
        "\n",
        "    # Fetch last layer's hidden_state for [\\CLIP OUT] tokens\n",
        "    last_hiddens = []\n",
        "    for idx in embedding_ids:\n",
        "        tok_count = torch.sum(targets_mask[idx])                      # Use original position since we concatenated an additional token\n",
        "        pos = (tok_count - abs(clip_pos[idx])) - 1                    # Subtract 1 since we shift targets\n",
        "        last_hiddens.append(outputs['hidden_states'][-1][idx][pos])\n",
        "        \n",
        "    caption_to_clip_loss = criterion_ce(outputs['logits'][embedding_ids, :-1].view(-1, outputs['logits'].size(-1)), target_clip_ids[embedding_ids, 1:].view(-1)) \\\n",
        "                            + criterion_mse(torch.stack(last_hiddens, dim=0).to(device), embs[embedding_ids].to(device))\n",
        "    clip_to_caption_loss = torch.nn.functional.cross_entropy(outputs['logits'][captioning_ids, :-1].reshape(-1, outputs['logits'].size(-1)), targets_ids[captioning_ids].flatten(), ignore_index=0)\n",
        "\n",
        "    loss = caption_to_clip_loss + clip_to_caption_loss\n",
        "\n",
        "    return loss\n",
        "\n",
        "\n",
        "def tune_caption_to_CLIP(model, tokenizer, optimizer, scheduler, dataloader, epochs=5):\n",
        "    \n",
        "    model.train()\n",
        "    for epoch in range(epochs):\n",
        "       \n",
        "        print(f\"Training epoch: {epoch}\")\n",
        "        num_batches = len(dataloader)\n",
        "\n",
        "        for batch_idx, (caps, _, embs, clip_pos) in  tqdm(enumerate(dataloader)):\n",
        "\n",
        "            optimizer.zero_grad()\n",
        "\n",
        "            loss = train_lm(model, tokenizer, caps, embs, clip_pos)\n",
        "            loss.backward()\n",
        "\n",
        "            optimizer.step()\n",
        "            scheduler.step()\n",
        "            \n",
        "            if batch_idx % 1000 == 0 and batch_idx != 0:\n",
        "                print(f\"Loss at batch {batch_idx} / {num_batches}  = {loss}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "viyMFqJK2qtZ"
      },
      "outputs": [],
      "source": [
        "coco_dataloader = DataLoader(coco_dataset, batch_size=16, shuffle=True, collate_fn=collate_fn)\n",
        "\n",
        "epochs = 5\n",
        "optimizer = torch.optim.AdamW(model.parameters(), lr=1e-4)\n",
        "scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps=2000, num_training_steps=epochs * len(coco_dataloader))\n",
        "\n",
        "tune_caption_to_CLIP(model, tokenizer, optimizer, scheduler, coco_dataloader, epochs=epochs)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Save Model and Tokenizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "tokenizer.save_pretrained(\"pretrained_tokenizers/gptLM-coco/\")\n",
        "model.save_pretrained(\"pretrained_models/gptLM-coco/\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tziPePvD2qtZ"
      },
      "source": [
        "### Load and KNN"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H7D524mW2qtZ"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "tokenizer = GPT2Tokenizer.from_pretrained(\"pretrained_tokenizers/gptLM-coco/\")\n",
        "\n",
        "model = GPT2LMHeadModel.from_pretrained(\"/content/pretrained_models/gptLM-coco/\").to(device)\n",
        "model.eval()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_VlwkaIv2qtZ"
      },
      "outputs": [],
      "source": [
        "def log_result(result):\n",
        "    id, caption, url, similarity = result[\"id\"], result[\"caption\"], result[\"url\"], result[\"similarity\"]\n",
        "    print(f\"id: {id}\")\n",
        "    print(f\"caption: {caption}\")\n",
        "    print(f\"url: {url}\")\n",
        "    print(f\"similarity: {similarity}\")\n",
        "    display(Image(url=url, unconfined=True))\n",
        "    \n",
        "    \n",
        "def nearest_im_neighbors(model, tokenizer, text, neighbors=None, clip_idx=None, k=5):\n",
        "    model.eval()\n",
        "\n",
        "    with torch.no_grad():\n",
        "        outputs = model.generate(**tokenizer(text, return_tensors='pt').to(device), return_dict_in_generate=True, output_hidden_states=True, max_new_tokens=50)\n",
        "        \n",
        "        if neighbors is not None:\n",
        "            print('Number of \"neighbors\": ', neighbors.shape[0], end=\"\\n\\n\")\n",
        "\n",
        "        print(\"Token ids: \", outputs['sequences'])\n",
        "        print(\"Token count: \", len(outputs['sequences'][0]), end=\"\\n\\n\")\n",
        "\n",
        "        print(\"Output text: \", tokenizer.decode(outputs['sequences'][0]))\n",
        "        print(f\"Token at index {clip_idx}: \", tokenizer.decode([outputs['sequences'][0][clip_idx]], skip_special_tokens=False), end=\"\\n\\n\")\n",
        "\n",
        "        print(\"Length of hidden states (number of new tokens): \", len(outputs['hidden_states']))\n",
        "        print(\"Number of hidden states: \", len(outputs['hidden_states'][-1]))\n",
        "        print(\"Size of a hidden state: \", outputs['hidden_states'][clip_idx][-1].size())\n",
        "\n",
        "        pred_emb = outputs['hidden_states'][clip_idx][-1][:,-1,:]\n",
        "        \n",
        "        if neighbors is not None:\n",
        "            # 1. Grab learned embedding from last hidden state if last layer for [\\CLIP OUT] token\n",
        "            # 2. Compute embedding similarities with all training embeddings\n",
        "            # 3. Retrieve top-k similarity image indices\n",
        "            topk_idx = torch.topk(torch.cosine_similarity(neighbors, pred_emb.cpu().detach(), dim=1), k).indices\n",
        "\n",
        "            for idx in topk_idx:\n",
        "                image_id = coco_dataset.file_id_dict[idx.item()]\n",
        "                I = io.imread(coco_dataset.coco_captions.loadImgs(image_id)[0]['coco_url'])\n",
        "                plt.axis('off')\n",
        "                plt.imshow(I)\n",
        "                plt.show()\n",
        "        else:\n",
        "            print(\"\\nFetching most similar image from LAION ...\")\n",
        "            pred_emb /= pred_emb.norm(dim=-1, keepdim=True)\n",
        "            pred_emb = pred_emb.cpu().detach().numpy().astype(\"float32\")[0]   \n",
        "            client = ClipClient(url=\"https://knn.laion.ai/knn-service\",\n",
        "                                indice_name=\"laion5B-L-14\",\n",
        "                                aesthetic_score=9,\n",
        "                                aesthetic_weight=0.5,\n",
        "                                modality=Modality.IMAGE,\n",
        "                                num_images=10,\n",
        "                                )\n",
        "            laion_results = client.query(embedding_input=pred_emb.tolist())\n",
        "            log_result(laion_results[0])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A9LB1zvrY6cc"
      },
      "source": [
        "KNN on COCO"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "text = \"Caption: [A children's birthday party.].\"\n",
        "nearest_im_neighbors(model, tokenizer, text, coco_images_tensor, clip_idx=-3, k=3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sgxznCMvZHKd"
      },
      "source": [
        "KNN on LAION-5B"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Euf4DVN8Y5Jd"
      },
      "outputs": [],
      "source": [
        "nearest_im_neighbors(model, tokenizer, text, clip_idx=-3, k=3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "59dcXabZ2qta"
      },
      "source": [
        "### Generate caption from image CLIP embedding"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1pJnMLsJ2qta"
      },
      "outputs": [],
      "source": [
        "# From https://github.com/rmokady/CLIP_prefix_caption/blob/main/predict.py\n",
        "def greedy_generate(\n",
        "    model,\n",
        "    tokenizer,\n",
        "    tokens=None,\n",
        "    prompt=None,\n",
        "    embed=None,\n",
        "    entry_count=1,\n",
        "    entry_length=67,  # maximum number of words\n",
        "    top_p=0.8,\n",
        "    temperature=1.0,\n",
        "    stop_token: str = \".\",\n",
        "):\n",
        "    model.eval()\n",
        "    generated_num = 0\n",
        "    generated_list = []\n",
        "    stop_token_index = tokenizer.encode(stop_token)[0]\n",
        "    filter_value = -float(\"Inf\")\n",
        "    device = next(model.parameters()).device\n",
        "\n",
        "    with torch.no_grad():\n",
        "\n",
        "        for entry_idx in range(entry_count):\n",
        "            if embed is not None:\n",
        "                generated = embed\n",
        "            else:\n",
        "                if tokens is None:\n",
        "                    tokens = torch.tensor(tokenizer.encode(prompt))\n",
        "                    tokens = tokens.unsqueeze(0).to(device)\n",
        "\n",
        "                generated = model.transformer.wte(tokens)\n",
        "\n",
        "            for i in range(entry_length):\n",
        "                generated = generated.to(device)\n",
        "                outputs = model(inputs_embeds=generated)\n",
        "                logits = outputs.logits\n",
        "                logits = logits[:, -1, :] / (temperature if temperature > 0 else 1.0)\n",
        "                sorted_logits, sorted_indices = torch.sort(logits, descending=True)\n",
        "                cumulative_probs = torch.cumsum(\n",
        "                    torch.nn.functional.softmax(sorted_logits, dim=-1), dim=-1\n",
        "                )\n",
        "                sorted_indices_to_remove = cumulative_probs > top_p\n",
        "                sorted_indices_to_remove[..., 1:] = sorted_indices_to_remove[\n",
        "                    ..., :-1\n",
        "                ].clone()\n",
        "                sorted_indices_to_remove[..., 0] = 0\n",
        "\n",
        "                indices_to_remove = sorted_indices[sorted_indices_to_remove]\n",
        "                logits[:, indices_to_remove] = filter_value\n",
        "                next_token = torch.argmax(logits, -1).unsqueeze(0)\n",
        "                next_token_embed = model.transformer.wte(next_token)\n",
        "                if tokens is None:\n",
        "                    tokens = next_token\n",
        "                else:\n",
        "                    tokens = torch.cat((tokens, next_token), dim=1)\n",
        "                generated = torch.cat((generated, next_token_embed), dim=1)\n",
        "                if stop_token_index == next_token.item():\n",
        "                    break\n",
        "\n",
        "            output_list = list(tokens.squeeze().cpu().numpy())\n",
        "            output_text = tokenizer.decode(output_list)\n",
        "            generated_list.append(output_text)\n",
        "\n",
        "    return generated_list[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FXQz71aC2qta",
        "outputId": "00ffaa34-17e0-409f-cc16-7bb22480ae60"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Original caption within modified text: [CLIP IN] [\\CLIP IN] Caption: [A stove top is cleaned with a set of knives on the wall.].\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Generate text from input image CLIP embedding:\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "'[\\\\CLIP IN] Caption: [A stove with a microwave above it and a toaster oven.].<|endoftext|>'"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "test_id = 89\n",
        "\n",
        "print(\"Original caption within modified text:\", coco_dataset.coco_data[test_id][0])\n",
        "\n",
        "I = io.imread(coco_dataset.coco_captions.loadImgs(coco_dataset.coco_data[test_id][1])[0]['coco_url'])\n",
        "plt.axis('off')\n",
        "plt.imshow(I)\n",
        "plt.show()\n",
        "\n",
        "print(\"Generate text from input image CLIP embedding:\")\n",
        "greedy_generate(model, tokenizer, embed=coco_dataset.coco_data[test_id][2].reshape(1, 1, -1), stop_token=tokenizer.pad_token)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Q1peDnRe2qta"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [
        "ccz--bg-2qtZ"
      ],
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.9"
    },
    "vscode": {
      "interpreter": {
        "hash": "68e788a5346e2f2adc82dcddcd3c4893312d2e6357dfd1b2a5091cc9f2d26b2a"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}