cookbooks/maestro_florence2_visual_question_answering.ipynb

{
    "cells": [
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "0qGDdiBI2YIE"
            },
            "outputs": [],
            "source": [
                "import os\n",
                "\n",
                "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\""
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "TDVdhkOtJb7t"
            },
            "source": [
                "## Setup"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "F38iHAuKJfzp"
            },
            "source": [
                "### Configure your API keys\n",
                "\n",
                "To fine-tune Florence-2, you need to provide your HuggingFace Token and Roboflow API key. Follow these steps:\n",
                "\n",
                "- Open your [`HuggingFace Settings`](https://huggingface.co/settings) page. Click `Access Tokens` then `New Token` to generate new token.\n",
                "- Go to your [`Roboflow Settings`](https://app.roboflow.com/settings/api) page. Click `Copy`. This will place your private key in the clipboard.\n",
                "- In Colab, go to the left pane and click on `Secrets` (\ud83d\udd11).\n",
                "    - Store HuggingFace Access Token under the name `HF_TOKEN`.\n",
                "    - Store Roboflow API Key under the name `ROBOFLOW_API_KEY`."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "OLEC5yoEJi4J"
            },
            "source": [
                "### Select the runtime\n",
                "\n",
                "Let's make sure that we have access to GPU. We can use `nvidia-smi` command to do that. In case of any problems navigate to `Edit` -> `Notebook settings` -> `Hardware accelerator`, set it to `L4 GPU`, and then click `Save`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "EpaminvvJm3H",
                "outputId": "ddf83457-b7e0-4088-e6bc-3d9a1fb94e91"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "Thu Sep 26 09:25:11 2024       \n",
                        "+---------------------------------------------------------------------------------------+\n",
                        "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
                        "|-----------------------------------------+----------------------+----------------------+\n",
                        "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
                        "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
                        "|                                         |                      |               MIG M. |\n",
                        "|=========================================+======================+======================|\n",
                        "|   0  NVIDIA A100-SXM4-40GB          Off | 00000000:00:04.0 Off |                    0 |\n",
                        "| N/A   30C    P0              42W / 400W |      2MiB / 40960MiB |      0%      Default |\n",
                        "|                                         |                      |             Disabled |\n",
                        "+-----------------------------------------+----------------------+----------------------+\n",
                        "                                                                                         \n",
                        "+---------------------------------------------------------------------------------------+\n",
                        "| Processes:                                                                            |\n",
                        "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
                        "|        ID   ID                                                             Usage      |\n",
                        "|=======================================================================================|\n",
                        "|  No running processes found                                                           |\n",
                        "+---------------------------------------------------------------------------------------+\n"
                    ]
                }
            ],
            "source": [
                "!nvidia-smi"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "1EA4j12iJxfW"
            },
            "source": [
                "### Install dependencies"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "gq-vRquBwwbX",
                "outputId": "0589544f-ed9c-4a02-ec1e-298407cc6e0f"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\u001b[2K     \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m42.4/42.4 kB\u001b[0m \u001b[31m1.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K     \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m36.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m43.0/43.0 kB\u001b[0m \u001b[31m3.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m80.3/80.3 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m66.8/66.8 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m296.4/296.4 kB\u001b[0m \u001b[31m26.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m151.3/151.3 kB\u001b[0m \u001b[31m15.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m86.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m54.5/54.5 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[2K   \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m3.1/3.1 MB\u001b[0m \u001b[31m84.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
                        "\u001b[?25h  Building wheel for flash-attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
                    ]
                }
            ],
            "source": [
                "!pip install -q roboflow maestro==0.2.0rc5"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "0VwpMjR6J-EQ"
            },
            "source": [
                "## Download dataset"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "A0sQCgrUfCtj",
                "outputId": "ee625ef2-05da-4d65-8a8c-23024cb165cb"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "loading Roboflow workspace...\n",
                        "loading Roboflow project...\n"
                    ]
                },
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Downloading Dataset Version Zip in ChartQA-1 to jsonl:: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 823764/823764 [00:12<00:00, 63687.29it/s]"
                    ]
                },
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\n"
                    ]
                },
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "\n",
                        "Extracting Dataset Version Zip to ChartQA-1 in jsonl:: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 20826/20826 [00:03<00:00, 5802.45it/s]\n"
                    ]
                }
            ],
            "source": [
                "from google.colab import userdata\n",
                "from roboflow import Roboflow\n",
                "\n",
                "ROBOFLOW_API_KEY = userdata.get(\"ROBOFLOW_API_KEY\")\n",
                "rf = Roboflow(api_key=ROBOFLOW_API_KEY)\n",
                "\n",
                "version = rf.workspace(\"roboflow-jvuqo\").project(\"chartqa-6pz0e\").version(1)\n",
                "dataset = version.download(\"jsonl\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "DiBFaHHDKX2Q",
                "outputId": "c1d38f0f-07a8-4e48-de43-cdee6556f02f"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "{\"image\":\"872a5b2feb73815d838ca904d22f16eb_png.rf.c67792c44387699b291a46d487675b86.jpg\",\"prefix\":\"How many non-gaming apps were available in the App Store in 2020?\",\"suffix\":\"3420161\"}\n",
                        "{\"image\":\"e0b0ab26790096d94b6d5c01c1f5a586_png.rf.c67cb9d929bebfde204ac7e08526e3fd.jpg\",\"prefix\":\"What is the expected growth rate of the wearable mobile medical equipment market in China from 2015 to 2016?\",\"suffix\":\"99.2\"}\n",
                        "{\"image\":\"c94129b94e922ee5841c90c06eab483d_png.rf.c67bb6d80c1d35b8a8628a14c2602485.jpg\",\"prefix\":\"How many Croatian kunas were exported in 2017?\",\"suffix\":\"73\"}\n",
                        "{\"image\":\"3a8cbc3e0c936447d2042bb1d2a39046_png.rf.c679b59d2a33750ddff1a10ee0cb6d8c.jpg\",\"prefix\":\"What was the expected number of Facebook users in South Korea in 2025?\",\"suffix\":\"16.1\"}\n",
                        "{\"image\":\"3a8cbc3e0c936447d2042bb1d2a39046_png.rf.c679b59d2a33750ddff1a10ee0cb6d8c.jpg\",\"prefix\":\"How many people used Facebook in South Korea in 2019?\",\"suffix\":\"15\"}\n"
                    ]
                }
            ],
            "source": [
                "!head -n 5 {dataset.location}/train/annotations.jsonl"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "4oWYhvLgtWz3"
            },
            "source": [
                "**NOTE:** The downloaded dataset is in raw JSONL format. To remain consistent with the Florence-2 convention, we will prefix each prefix with the name of the vision task being performed. In our case, this will be `<VQA>`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "rOjgz_bdqhhZ"
            },
            "outputs": [],
            "source": [
                "import json\n",
                "import os\n",
                "from typing import Any\n",
                "\n",
                "\n",
                "def modify_jsonl(file_path: str, task: str) -> None:\n",
                "    \"\"\"Modify each line of a JSONL file by prepending a task string to the 'prefix' value.\n",
                "\n",
                "    Args:\n",
                "        file_path (str): Path to the JSONL file to modify.\n",
                "        task (str): The string to prepend to each 'prefix' value in the JSONL file.\n",
                "\n",
                "    Returns:\n",
                "        None\n",
                "    \"\"\"\n",
                "    temp_file_path: str = file_path + \".temp\"\n",
                "\n",
                "    with open(file_path) as infile, open(temp_file_path, \"w\") as outfile:\n",
                "        for line in infile:\n",
                "            data: dict[str, Any] = json.loads(line.strip())\n",
                "            data[\"prefix\"] = f\"{task}{data['prefix']}\"\n",
                "            outfile.write(json.dumps(data) + \"\\n\")\n",
                "\n",
                "    os.replace(temp_file_path, file_path)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "f02mJ08oqsWb"
            },
            "outputs": [],
            "source": [
                "modify_jsonl(f\"{dataset.location}/train/annotations.jsonl\", \"<VQA>\")\n",
                "modify_jsonl(f\"{dataset.location}/test/annotations.jsonl\", \"<VQA>\")\n",
                "modify_jsonl(f\"{dataset.location}/valid/annotations.jsonl\", \"<VQA>\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "GzBM-fX8q2HD",
                "outputId": "d91a2d9c-4432-4ed9-d3c3-1994174cbc1c"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "{\"image\": \"872a5b2feb73815d838ca904d22f16eb_png.rf.c67792c44387699b291a46d487675b86.jpg\", \"prefix\": \"<VQA>How many non-gaming apps were available in the App Store in 2020?\", \"suffix\": \"3420161\"}\n",
                        "{\"image\": \"e0b0ab26790096d94b6d5c01c1f5a586_png.rf.c67cb9d929bebfde204ac7e08526e3fd.jpg\", \"prefix\": \"<VQA>What is the expected growth rate of the wearable mobile medical equipment market in China from 2015 to 2016?\", \"suffix\": \"99.2\"}\n",
                        "{\"image\": \"c94129b94e922ee5841c90c06eab483d_png.rf.c67bb6d80c1d35b8a8628a14c2602485.jpg\", \"prefix\": \"<VQA>How many Croatian kunas were exported in 2017?\", \"suffix\": \"73\"}\n",
                        "{\"image\": \"3a8cbc3e0c936447d2042bb1d2a39046_png.rf.c679b59d2a33750ddff1a10ee0cb6d8c.jpg\", \"prefix\": \"<VQA>What was the expected number of Facebook users in South Korea in 2025?\", \"suffix\": \"16.1\"}\n",
                        "{\"image\": \"3a8cbc3e0c936447d2042bb1d2a39046_png.rf.c679b59d2a33750ddff1a10ee0cb6d8c.jpg\", \"prefix\": \"<VQA>How many people used Facebook in South Korea in 2019?\", \"suffix\": \"15\"}\n"
                    ]
                }
            ],
            "source": [
                "!head -n 5 {dataset.location}/train/annotations.jsonl"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "bgyVKInOKbxT"
            },
            "source": [
                "## Fine-tune Florence-2 on visual questions answering (VQA) dataset"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "GkMwxcXN09jx",
                "outputId": "6bab3292-ff6e-43d0-d4bb-dfdabe44d5a7"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\u001b[1m                                                                                                    \u001b[0m\n",
                        "\u001b[1m \u001b[0m\u001b[1;33mUsage: \u001b[0m\u001b[1mmaestro florence2 train [OPTIONS]\u001b[0m\u001b[1m                                                          \u001b[0m\u001b[1m \u001b[0m\n",
                        "\u001b[1m                                                                                                    \u001b[0m\n",
                        " Train Florence 2 model                                                                             \n",
                        "                                                                                                    \n",
                        "\u001b[2m\u256d\u2500\u001b[0m\u001b[2m Options \u001b[0m\u001b[2m\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u001b[0m\u001b[2m\u2500\u256e\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m \u001b[31m*\u001b[0m  \u001b[1;36m-\u001b[0m\u001b[1;36m-dataset\u001b[0m                                 \u001b[1;33mTEXT   \u001b[0m  Path to the dataset used for training      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: None]                      \u001b[0m      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2;31m[required]                           \u001b[0m      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-model_id\u001b[0m                                \u001b[1;33mTEXT   \u001b[0m  Identifier for the Florence-2 model        \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: microsoft/Florence-2-base-ft]\u001b[0m    \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-revision\u001b[0m                                \u001b[1;33mTEXT   \u001b[0m  Revision of the model to use               \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: refs/pr/20]       \u001b[0m               \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-device\u001b[0m                                  \u001b[1;33mTEXT   \u001b[0m  Device to use for training                 \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: cuda:0]         \u001b[0m                 \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-cache_dir\u001b[0m                               \u001b[1;33mTEXT   \u001b[0m  Directory to cache the model               \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: None]             \u001b[0m               \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-epochs\u001b[0m                                  \u001b[1;33mINTEGER\u001b[0m  Number of training epochs \u001b[2m[default: 10]\u001b[0m    \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-optimizer\u001b[0m                               \u001b[1;33mTEXT   \u001b[0m  Optimizer to use for training              \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: adamw]             \u001b[0m              \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-lr\u001b[0m                                      \u001b[1;33mFLOAT  \u001b[0m  Learning rate for the optimizer            \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: 1e-05]               \u001b[0m            \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-lr_scheduler\u001b[0m                            \u001b[1;33mTEXT   \u001b[0m  Learning rate scheduler \u001b[2m[default: linear]\u001b[0m  \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-batch_size\u001b[0m                              \u001b[1;33mINTEGER\u001b[0m  Batch size for training \u001b[2m[default: 4]\u001b[0m       \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-val_batch_size\u001b[0m                          \u001b[1;33mINTEGER\u001b[0m  Batch size for validation \u001b[2m[default: None]\u001b[0m  \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-num_workers\u001b[0m                             \u001b[1;33mINTEGER\u001b[0m  Number of workers for data loading         \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: 0]                      \u001b[0m         \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-val_num_workers\u001b[0m                         \u001b[1;33mINTEGER\u001b[0m  Number of workers for validation data      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       loading                                    \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: None]                           \u001b[0m \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-lora_r\u001b[0m                                  \u001b[1;33mINTEGER\u001b[0m  Rank of the LoRA update matrices           \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: 8]                    \u001b[0m           \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-lora_alpha\u001b[0m                              \u001b[1;33mINTEGER\u001b[0m  Scaling factor for the LoRA update         \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: 8]                      \u001b[0m         \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-lora_dropout\u001b[0m                            \u001b[1;33mFLOAT  \u001b[0m  Dropout probability for LoRA layers        \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: 0.05]                    \u001b[0m        \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-bias\u001b[0m                                    \u001b[1;33mTEXT   \u001b[0m  Which bias to train \u001b[2m[default: none]\u001b[0m        \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-use_rslora\u001b[0m           \u001b[1;35m-\u001b[0m\u001b[1;35m-no_use_rslora\u001b[0m    \u001b[1;33m       \u001b[0m  Whether to use RSLoRA                      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: use_rslora]\u001b[0m                      \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-init_lora_weights\u001b[0m                       \u001b[1;33mTEXT   \u001b[0m  How to initialize LoRA weights             \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: gaussian]           \u001b[0m             \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-output_dir\u001b[0m                              \u001b[1;33mTEXT   \u001b[0m  Directory to save output files             \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m                                                       \u001b[2m[default: ./training/florence-2]\u001b[0m           \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-metrics\u001b[0m                                 \u001b[1;33mTEXT   \u001b[0m  List of metrics to track during training   \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2502\u001b[0m    \u001b[1;36m-\u001b[0m\u001b[1;36m-help\u001b[0m                                    \u001b[1;33m       \u001b[0m  Show this message and exit.                \u001b[2m\u2502\u001b[0m\n",
                        "\u001b[2m\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\u001b[0m\n",
                        "\n"
                    ]
                }
            ],
            "source": [
                "!maestro florence2 train --help"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "-9IlCLXepqTv"
            },
            "outputs": [],
            "source": [
                "!maestro florence2 train --dataset={dataset.location} \\\n",
                "--epochs=3 --batch_size=14 --lr=2e-6 \\\n",
                "--metrics word_error_rate --metrics character_error_rate"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "5-cECkMgRt3R"
            },
            "source": [
                "## Evaluate Florence-2 on visual questions answering (VQA) dataset"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "7_3QQrw6PCip",
                "outputId": "ceb0afac-e109-46d0-fdfd-ac74794ca68f"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "total 776\n",
                        "drwxr-xr-x 2 root root   4096 Sep 26 12:31 .\n",
                        "drwxr-xr-x 4 root root   4096 Sep 26 12:31 ..\n",
                        "-rw-r--r-- 1 root root  31661 Sep 26 12:31 cer_plot.png\n",
                        "-rw-r--r-- 1 root root  33816 Sep 26 12:31 loss_plot.png\n",
                        "-rw-r--r-- 1 root root 667912 Sep 26 12:31 training.json\n",
                        "-rw-r--r-- 1 root root   1030 Sep 26 12:31 validation.json\n",
                        "-rw-r--r-- 1 root root  38340 Sep 26 12:31 wer_plot.png\n"
                    ]
                }
            ],
            "source": [
                "!ls -la training/florence-2/1/metrics/"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/",
                    "height": 617
                },
                "id": "qC_blu2c0x6z",
                "outputId": "0796f7d6-87ce-46ce-be89-dac065c46cdb"
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<IPython.core.display.Image object>"
                        ]
                    },
                    "execution_count": 12,
                    "metadata": {
                        "image/png": {
                            "height": 600
                        }
                    },
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "from IPython.display import Image\n",
                "\n",
                "Image(filename=\"training/florence-2/1/metrics/loss_plot.png\", height=600)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/",
                    "height": 617
                },
                "id": "GnZlFHrh1gzm",
                "outputId": "f41f675e-ffcf-4fbb-d5fd-6e71ecf1171c"
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<IPython.core.display.Image object>"
                        ]
                    },
                    "execution_count": 13,
                    "metadata": {
                        "image/png": {
                            "height": 600
                        }
                    },
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "from IPython.display import Image\n",
                "\n",
                "Image(filename=\"training/florence-2/1/metrics/wer_plot.png\", height=600)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/",
                    "height": 617
                },
                "id": "z66qE-1aM7OK",
                "outputId": "ae04443f-f6c2-4bab-9118-71bd5023d375"
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<IPython.core.display.Image object>"
                        ]
                    },
                    "execution_count": 14,
                    "metadata": {
                        "image/png": {
                            "height": 600
                        }
                    },
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "from IPython.display import Image\n",
                "\n",
                "Image(filename=\"training/florence-2/1/metrics/cer_plot.png\", height=600)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "m5V4J4JJNDOv",
                "outputId": "41e3914f-6419-4da5-bc3f-571e41984eb6"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "total 16\n",
                        "drwxr-xr-x 4 root root 4096 Sep 26 10:30 .\n",
                        "drwxr-xr-x 4 root root 4096 Sep 26 12:31 ..\n",
                        "drwxr-xr-x 2 root root 4096 Sep 26 10:30 best\n",
                        "drwxr-xr-x 2 root root 4096 Sep 26 10:30 latest\n"
                    ]
                }
            ],
            "source": [
                "!ls -la training/florence-2/1/checkpoints/"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "Oc3Kuk_Yt5Ut"
            },
            "outputs": [],
            "source": [
                "!maestro florence2 evaluate \\\n",
                "--dataset={dataset.location} \\\n",
                "--model_id=/content/training/florence-2/1/checkpoints/best \\\n",
                "--metrics word_error_rate --metrics character_error_rate"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "uoJIQVDv2BkN",
                "outputId": "b9e735c4-d31b-4547-f8ee-3293b639186f"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "{\n",
                        "    \"wer\": [\n",
                        "        {\n",
                        "            \"epoch\": 1,\n",
                        "            \"step\": 1,\n",
                        "            \"value\": 0.9083285714285714\n",
                        "        }\n",
                        "    ],\n",
                        "    \"cer\": [\n",
                        "        {\n",
                        "            \"epoch\": 1,\n",
                        "            \"step\": 1,\n",
                        "            \"value\": 2.5642966056790737\n",
                        "        }\n",
                        "    ]\n",
                        "}"
                    ]
                }
            ],
            "source": [
                "!cat /content/evaluation/florence-2/metrics/evaluation.json"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {
                "id": "k9IOnjDER2JW"
            },
            "source": [
                "## Run inference"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "id": "SKwCDU1cQVXq"
            },
            "outputs": [],
            "source": [
                "from maestro.trainer.models.florence_2.checkpoints import load_model\n",
                "\n",
                "processor, model = load_model(model_id_or_path=\"/content/training/florence-2/1/checkpoints/best\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/"
                },
                "id": "E8Q-A7sS1pHB",
                "outputId": "fa8f5589-ef2e-41e5-857a-f46c0f49429e"
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "question: <VQA>What company had a 21.2 percent share of the Indonesian mobile phone market in the first quarter of 2015?\n",
                        "answare: Samsung\n"
                    ]
                }
            ],
            "source": [
                "from maestro.trainer.common.data_loaders.datasets import JSONLDataset\n",
                "\n",
                "ds = JSONLDataset(\n",
                "    jsonl_file_path=f\"{dataset.location}/valid/annotations.jsonl\", image_directory_path=f\"{dataset.location}/valid/\"\n",
                ")\n",
                "\n",
                "image, annotations = ds[0]\n",
                "text = annotations[\"prefix\"]\n",
                "\n",
                "inputs = processor(text=text, images=image, return_tensors=\"pt\").to(\"cuda\")\n",
                "generated_ids = model.generate(\n",
                "    input_ids=inputs[\"input_ids\"], pixel_values=inputs[\"pixel_values\"], max_new_tokens=1024, num_beams=3\n",
                ")\n",
                "generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]\n",
                "print(\"question:\", text)\n",
                "print(\"answare:\", generated_text)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "colab": {
                    "base_uri": "https://localhost:8080/",
                    "height": 574
                },
                "id": "gNMfBrQglHd1",
                "outputId": "fac9850e-408f-476c-ff80-7880fe22d557"
            },
            "outputs": [
                {
                    "data": {
                        "image/jpeg": 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\n",
                        "text/plain": [
                            "<PIL.Image.Image image mode=RGB size=800x557>"
                        ]
                    },
                    "execution_count": 25,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "image"
            ]
        }
    ],
    "metadata": {
        "accelerator": "GPU",
        "colab": {
            "gpuType": "A100",
            "machine_shape": "hm",
            "provenance": []
        },
        "kernelspec": {
            "display_name": "Python 3",
            "name": "python3"
        },
        "language_info": {
            "name": "python"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 0
}