notebooks/example_bootstrap.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/urmzd/lepus-classifier/blob/main/notebooks/example_bootstrap.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IVp9C5yO9UOs",
        "outputId": "1057e32d-762f-43ae-90db-a6a775f4cb2d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cloning into 'lepus-classifier'...\n",
            "remote: Enumerating objects: 1161, done.\u001b[K\n",
            "remote: Counting objects: 100% (1161/1161), done.\u001b[K\n",
            "remote: Compressing objects: 100% (724/724), done.\u001b[K\n",
            "remote: Total 1161 (delta 654), reused 762 (delta 337), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (1161/1161), 52.73 MiB | 9.35 MiB/s, done.\n",
            "Resolving deltas: 100% (654/654), done.\n"
          ]
        }
      ],
      "source": [
        "!rm -rf /content/*\n",
        "!git clone https://github.com/urmzd/lepus-classifier"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QGf8ycHluwZh",
        "outputId": "2af6fbf0-f431-4942-bd37-07ef316bace0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "\u001b[?25hCollecting aiosignal>=1.1.2\n",
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            "  Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB)\n",
            "Building wheels for collected packages: pipetools, pathtools\n",
            "  Building wheel for pipetools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pipetools: filename=pipetools-1.1.0-py3-none-any.whl size=13621 sha256=0ff99e43e2e1739eba01032af24ac90ef82e96a82399a89ad9d89510f320c016\n",
            "  Stored in directory: /root/.cache/pip/wheels/db/e4/55/098fde0def89ca29d2cf30f27b19e299c835ce2a08fcc592d6\n",
            "  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pathtools: filename=pathtools-0.1.2-py3-none-any.whl size=8806 sha256=d1c4b4e6708e8d423fe7ce5fdb5aa5f59e539f538afe2b638585388ddb4595b0\n",
            "  Stored in directory: /root/.cache/pip/wheels/3e/31/09/fa59cef12cdcfecc627b3d24273699f390e71828921b2cbba2\n",
            "Successfully built pipetools pathtools\n",
            "Installing collected packages: typing-extensions, multidict, frozenlist, yarl, smmap, asynctest, async-timeout, aiosignal, pyDeprecate, gitdb, fsspec, aiohttp, yaspin, torchmetrics, shortuuid, setproctitle, sentry-sdk, PyYAML, pathtools, GitPython, docker-pycreds, wandb, pytorch-lightning, pipetools, loguru\n",
            "  Attempting uninstall: typing-extensions\n",
            "    Found existing installation: typing-extensions 3.10.0.2\n",
            "    Uninstalling typing-extensions-3.10.0.2:\n",
            "      Successfully uninstalled typing-extensions-3.10.0.2\n",
            "  Attempting uninstall: PyYAML\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tensorflow 2.8.0 requires tf-estimator-nightly==2.8.0.dev2021122109, which is not installed.\n",
            "arviz 0.11.4 requires typing-extensions<4,>=3.7.4.3, but you have typing-extensions 4.1.1 which is incompatible.\u001b[0m\n",
            "Successfully installed GitPython-3.1.27 PyYAML-6.0 aiohttp-3.8.1 aiosignal-1.2.0 async-timeout-4.0.2 asynctest-0.13.0 docker-pycreds-0.4.0 frozenlist-1.2.0 fsspec-2022.3.0 gitdb-4.0.9 loguru-0.6.0 multidict-6.0.2 pathtools-0.1.2 pipetools-1.1.0 pyDeprecate-0.3.2 pytorch-lightning-1.6.0 sentry-sdk-1.5.1 setproctitle-1.2.2 shortuuid-1.0.8 smmap-5.0.0 torchmetrics-0.7.3 typing-extensions-4.1.1 wandb-0.12.11 yarl-1.7.2 yaspin-2.1.0\n",
            "Collecting pyyaml==5.4.1\n",
            "  Downloading PyYAML-5.4.1-cp37-cp37m-manylinux1_x86_64.whl (636 kB)\n",
            "\u001b[K     |████████████████████████████████| 636 kB 5.0 MB/s \n",
            "\u001b[?25hInstalling collected packages: pyyaml\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 6.0\n",
            "    Uninstalling PyYAML-6.0:\n",
            "      Successfully uninstalled PyYAML-6.0\n",
            "Successfully installed pyyaml-5.4.1\n"
          ]
        }
      ],
      "source": [
        "!pip install wandb pytorch-lightning pipetools loguru -q \n",
        "!pip install pyyaml==5.4.1 -q"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nbxsYC9z0HeX",
        "outputId": "301e5eb3-2be9-4a99-f0a2-1b4250215cea"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter, or press ctrl+c to quit: \n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
          ]
        }
      ],
      "source": [
        "!wandb login"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "Snr8mEV_wEJT"
      },
      "outputs": [],
      "source": [
        "import sys\n",
        "SRC_PATH = \"/content/lepus-classifier\"\n",
        "sys.path.insert(0, SRC_PATH)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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          "referenced_widgets": [
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        },
        "id": "NfgCcEKdxG7H",
        "outputId": "b212332d-2274-45a3-fad3-dea53a47fde8"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/distributed/config.py:20: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n",
            "  defaults = yaml.load(f)\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mcsci-4155-rabbit-classifier\u001b[0m (use `wandb login --relogin` to force relogin)\n"
          ]
        },
        {
          "data": {
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              "Tracking run with wandb version 0.12.11"
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          "data": {
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20220405_153704-15m7nc3u</code>"
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            "Global seed set to 42\n",
            "GPU available: False, used: False\n",
            "TPU available: False, using: 0 TPU cores\n",
            "IPU available: False, using: 0 IPUs\n",
            "HPU available: False, using: 0 HPUs\n",
            "\n",
            "  | Name          | Type       | Params\n",
            "---------------------------------------------\n",
            "0 | layer_1       | Conv2d     | 75    \n",
            "1 | layer_2       | MaxPool2d  | 0     \n",
            "2 | layer_3       | ReLU       | 0     \n",
            "3 | layer_4       | Flatten    | 0     \n",
            "4 | layer_5       | Linear     | 75.0 K\n",
            "5 | softmax_layer | LogSoftmax | 0     \n",
            "---------------------------------------------\n",
            "75.1 K    Trainable params\n",
            "0         Non-trainable params\n",
            "75.1 K    Total params\n",
            "0.300     Total estimated model params size (MB)\n",
            "2022-04-05 15:37:08.703 | INFO     | src.data.data_handler:on_advance_start:213 - STARTING FOLD 0\n",
            "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/connectors/data_connector.py:245: PossibleUserWarning: The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 4 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
            "  category=PossibleUserWarning,\n",
            "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py:1942: PossibleUserWarning: The number of training samples (27) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n",
            "  category=PossibleUserWarning,\n",
            "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/connectors/data_connector.py:245: PossibleUserWarning: The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 4 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
            "  category=PossibleUserWarning,\n"
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            "/content/lepus-classifier/src/data/data_handler.py:294: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n",
            "  result = self.softmax_layer(x_5)\n"
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        "from pytorch_lightning.loggers import WandbLogger\n",
        "\n",
        "trainer_factory = TrainerFactory(\n",
        "    max_epochs=5, \n",
        ")\n",
        "\n",
        "bootstrap(\n",
        "    trainer_factory=trainer_factory,\n",
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