{
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   "execution_count": 1,
   "id": "4c6f353f-83e2-4780-9124-bf7f30e2a77d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from typing import Optional\n",
    "\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "\n",
    "import wandb\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from transformers import T5TokenizerFast, T5ForConditionalGeneration\n",
    "\n",
    "from _config import load_config\n",
    "from _utils import print_system_info, silent_logs\n",
    "from _datasets import AutoLoad, generate_dataloader\n",
    "from _mydelta import T5Wrapper, auto_freeze, EmbeddingWrapper\n",
    "from _trainer import train_loop, valid_loop, BestFinder\n",
    "\n",
    "# configs = load_config('./config.yaml')\n",
    "\n",
    "# RANDOM_SEED = configs.shared.random_seed\n",
    "# WANDB_PROJECT_NAME = configs.shared.project_name\n",
    "# DEVICE = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "# USE_TQDM = configs.shared.use_tqdm\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ead0c663-c9e4-4625-8f3b-11e53ca59920",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = T5ForConditionalGeneration.from_pretrained('google/t5-large-lm-adapt')\n",
    "tokenizer = T5TokenizerFast.from_pretrained('google/t5-large-lm-adapt', model_max_length=2048)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e348f601-c713-49af-86e4-a40382c5a36f",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_tokens = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d9a6602-f90d-440a-b11e-ddda2d36d2f7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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