{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Google Colab Training Notebook\n",
        "\n",
        "This notebook is intended to be run on Google Colab with a T4 GPU. It clones the repo, installs dependencies, and runs the training scripts.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "!git clone https://github.com/Aryanmishra-dev/Multilingual-Absa.git\n",
        "%cd Multilingual-Absa\n",
        "!pip install .\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Mount Google Drive to save models and MLflow logs persistently\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Create symlinks or copy data if needed\n",
        "# Assuming data is in the repo for now\n",
        "!mkdir -p /content/drive/MyDrive/ABSA_models\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Prepare dataset\n",
        "!PYTHONPATH=src python -m absa.data.hf_dataset\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Run Aspect Extraction Training\n",
        "!PYTHONPATH=src python -m absa.models.train_aspect_extraction\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Run Sentiment Classification Training\n",
        "!PYTHONPATH=src python -m absa.models.train_sentiment\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Run Baseline as well\n",
        "!PYTHONPATH=src python -m absa.models.baseline\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Cross-lingual Evaluation\n",
        "!PYTHONPATH=src python -m absa.evaluation.cross_lingual_eval\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "source": [
        "# Copy models back to Drive\n",
        "!cp -r models/* /content/drive/MyDrive/ABSA_models/\n",
        "!cp -r mlflow /content/drive/MyDrive/ABSA_models/\n"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.11.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}