{
 "cells": [
  {
   "cell_type": "code",
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   "metadata": {},
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   "source": [
    "import torch\n",
    "\n",
    "def load_checkpoint(filepath: str) -> dict:\n",
    "    \"\"\"\n",
    "    Load a checkpoint file.\n",
    "\n",
    "    Args:\n",
    "    filepath (str): Path to the .ckpt file.\n",
    "\n",
    "    Returns:\n",
    "    dict: Contents of the checkpoint file.\n",
    "    \"\"\"\n",
    "    checkpoint = torch.load(filepath, map_location=torch.device('cpu'))\n",
    "    return checkpoint\n",
    "\n",
    "checkpoint_path = 'ckpt.pt'\n",
    "checkpoint_data = load_checkpoint(checkpoint_path)\n",
    "\n",
    "# Print the keys to understand what's inside\n",
    "print(checkpoint_data.keys())\n",
    "\n",
    "# If you want to view specific information, access it using the keys\n",
    "# For example, to view the model's state_dict\n",
    "model_state = checkpoint_data.get('state_dict', None)\n",
    "if model_state:\n",
    "    print(\"Model's state dict:\", model_state)\n",
    "\n",
    "# To view training information like current learning rate, iterations, etc.\n",
    "training_info = checkpoint_data.get('training_info', None)\n",
    "if training_info:\n",
    "    print(\"Training Info:\", training_info)\n",
    "\n",
    "# To view config, if it's stored in the checkpoint\n",
    "config = checkpoint_data.get('config', None)\n",
    "if config:\n",
    "    print(\"Configurations:\", config)\n"
   ]
  }
 ],
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