integrations-and-supported-tools/colab/Neptune_Colab.ipynb

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    "![Neptune + Colab](https://neptune.ai/wp-content/uploads/2023/09/colab.svg)\n",
    "\n",
    "# Neptune + Google Colab\n",
    "\n",
    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/colab/Neptune_Colab.ipynb\">\n",
    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\"/>\n",
    "</a><a target=\"_blank\" href=\"https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/colab/Neptune_Colab.ipynb\">\n",
    "  <img alt=\"Open in GitHub\" src=\"https://img.shields.io/badge/Open_in_GitHub-blue?logo=github&labelColor=black\">\n",
    "</a><a target=\"_blank\" href=\"https://app.neptune.ai/o/common/org/showroom/e/SHOW-37/charts\"> \n",
    "  <img alt=\"Explore in Neptune\" src=\"https://neptune.ai/wp-content/uploads/2024/01/neptune-badge.svg\">\n",
    "</a><a target=\"_blank\" href=\"https://docs.neptune.ai/integrations/colab/\">\n",
    "  <img alt=\"View tutorial in docs\" src=\"https://neptune.ai/wp-content/uploads/2024/01/docs-badge-2.svg\">\n",
    "</a>"
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   "source": [
    "## Introduction"
   ]
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   "source": [
    "This guide will show you how to:\n",
    "\n",
    "* Install `neptune`,\n",
    "* Connect Neptune to your Colab notebook and create the first run,\n",
    "* Log simple metrics to Neptune and explore them in the web app."
   ]
  },
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   "source": [
    "## Before you start\n",
    "\n",
    "Make sure that you have a [Google account](https://support.google.com/accounts/answer/27441?hl=en).\n",
    "\n",
    "If you want to see the example logged to your own workspace instead:\n",
    "\n",
    "  1. Create a Neptune account. [Register &rarr;](https://neptune.ai/register)\n",
    "  1. Create a Neptune project that you will use for tracking metadata. For instructions, see [Creating a project](https://docs.neptune.ai/setup/creating_project) in the Neptune docs."
   ]
  },
  {
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   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "header",
     "installation"
    ]
   },
   "source": [
    "## Install Neptune and dependencies"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
    "tags": [
     "installation"
    ]
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   "outputs": [],
   "source": [
    "! pip install neptune"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import neptune"
   ]
  },
  {
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   },
   "source": [
    "## Initialize Neptune"
   ]
  },
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   "source": [
    "To create a new run for tracking the metadata, you tell Neptune who you are (with the API token) and where to send the data (your project).\n",
    "\n",
    "To find your API token:\n",
    "\n",
    "1. [Log in to Neptune](https://app.neptune.ai/).\n",
    "1. In the bottom-left corner, expand your user menu and select **Get your API token**.\n",
    "\n",
    "For more help, see [Setting Neptune credentials](https://docs.neptune.ai/setup/setting_credentials) in the Neptune docs.\n",
    "\n",
    "### Logging anonymously\n",
    "\n",
    "Replace the code below with the following:\n",
    "\n",
    "```python\n",
    "api_token = neptune.ANONYMOUS_API_TOKEN\n",
    "```\n",
    "\n",
    "**Note**: Public projects are cleaned regularly, so anonymous runs are only stored temporarily."
   ]
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  {
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   "metadata": {
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   "source": [
    "from getpass import getpass\n",
    "\n",
    "api_token = getpass(\"Enter your private Neptune API token: \")"
   ]
  },
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   "source": [
    "### Initialize your project\n",
    "\n",
    "If you haven't already, [create a new project](https://docs.neptune.ai/setup/creating_project) that you will use for metadata tracking.\n",
    "\n",
    "You need to give the full project name, in the form `workspace-name/project-name`.\n",
    "\n",
    "To copy the project path, open the settings menu and select **Details & privacy**."
   ]
  },
  {
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   "source": [
    "workspace = \"YOUR_WORKSPACE\"  # replace with your own\n",
    "project_name = \"YOUR_PROJECT\"  # replace\n",
    "project = f\"{workspace}/{project_name}\"\n",
    "\n",
    "# if you are using ANONYMOUS api token, log to the project 'common/neptune-and-google-colab'\n",
    "# project = 'common/neptune-and-google-colab'\n",
    "\n",
    "print(project)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "We're ready to initialize a Neptune run."
   ]
  },
  {
   "cell_type": "code",
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   "outputs": [],
   "source": [
    "run = neptune.init_run(\n",
    "    project=project,\n",
    "    api_token=api_token,\n",
    "    capture_hardware_metrics=True,\n",
    "    capture_stderr=True,\n",
    "    capture_stdout=True,\n",
    ")  # Hardware metrics, stderr, and stdout are not captured by default in interactive kernels"
   ]
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   "source": [
    "**To open the run in the Neptune web app, click the link that appeared in the cell output.**\n",
    "\n",
    "We'll use the `run` object we just created to log metadata. You'll see the metadata appear in the app."
   ]
  },
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   "source": [
    "Runs can be viewed as dictionary-like structures - **namespaces** - that you can define in your code. You can apply a hierarchical structure to your metadata that will be reflected in the UI as well. Thanks to this you can easily organize your metadata in a way you feel is most convenient."
   ]
  },
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   "source": [
    "## Log metadata during training"
   ]
  },
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    ]
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   "source": [
    "Log metrics or losses under a name of your choice. You can log one or multiple values.\n",
    "\n",
    "Now run the cell below, and switch over to the Neptune app to view the live logging."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "code"
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   "source": [
    "from time import sleep\n",
    "\n",
    "params = {\"learning_rate\": 0.1}\n",
    "\n",
    "# log params\n",
    "run[\"parameters\"] = params\n",
    "\n",
    "# log name and append tags\n",
    "run[\"sys/name\"] = \"colab-example\"\n",
    "run[\"sys/tags\"].add([\"colab\", \"simple\"])\n",
    "\n",
    "# log loss during training\n",
    "for epoch in range(132):\n",
    "    sleep(0.1)  # to see logging live\n",
    "    run[\"train/loss\"].append(0.97**epoch)\n",
    "    run[\"train/loss-pow-2\"].append((0.97**epoch) ** 2)\n",
    "\n",
    "# log train and validation scores\n",
    "run[\"train/accuracy\"] = 0.95\n",
    "run[\"valid/accuracy\"] = 0.93\n",
    "\n",
    "# log files/artifacts\n",
    "! echo \"Welcome to Neptune\" > file.txt\n",
    "run[\"artifacts/sample\"].upload(\"file.txt\")  # file will be uploaded as sample.txt"
   ]
  },
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   "source": [
    "The snippet above logs:\n",
    "\n",
    "* `parameters` with just one field: learning rate,\n",
    "* name of run and two tags,\n",
    "* `train/loss` and `train/loss-pow-2` as series of numbers, visualized as charts in UI,\n",
    "* `train/accuracy` and `valid/accuracy` as single values\n",
    "* `file.txt` which will be visible under All Metadata/artifacts as sample.txt"
   ]
  },
  {
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   "source": [
    "**Tip:**<br>\n",
    "To view the structure of a run, use the `print_structure()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "run.print_structure()"
   ]
  },
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   "source": [
    "## Stop logging  \n",
    "<font color=red>**Warning:**</font><br>\n",
    "Once you are done logging, you should stop tracking the run using the `stop()` method.\n",
    "This is needed only while logging from a notebook environment. While logging through a script, Neptune automatically stops tracking once the script has completed execution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "run.stop()"
   ]
  },
  {
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   },
   "source": [
    "## Explore the run in the Neptune app\n",
    "\n",
    "Go to the **All metadata** and **Charts** sections of the Neptune app to see them. You can also check an [example run](https://app.neptune.ai/o/common/org/showroom/e/SHOW-37/charts).\n",
    "\n",
    "You can see the hardware consumption in the **Monitoring** section of the Neptune app."
   ]
  },
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   "source": [
    "## Conclusion\n",
    "\n",
    "You’ve learned how to:\n",
    "* Install `neptune`,\n",
    "* Connect Neptune to your Google Colab notebook and create a run,\n",
    "* Log metadata to Neptune,\n",
    "* See your metrics parameters and scores,\n",
    "* See hardware consumption during the run."
   ]
  },
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   "source": [
    "## What's next\n",
    "\n",
    "Now that you know how to create runs and log metrics, you can learn:\n",
    "\n",
    "* [How to log other types of metadata to Neptune](https://docs.neptune.ai/logging/what_you_can_log/)\n",
    "* [How to download runs data from Neptune](https://docs.neptune.ai/usage/querying_metadata/)\n",
    "* [How to connect Neptune to the ML framework you are using](https://docs.neptune.ai/essentials/integrations)"
   ]
  }
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