Upload BAAO.ipynb

BAAO.ipynb

@@ -0,0 +1,1809 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Rs8s9i7fVhAB",
+        "outputId": "672c9f33-75eb-4a20-a36d-fa9be2110cc6"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.35.0)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.1)\n",
+            "Requirement already satisfied: huggingface-hub<1.0,>=0.16.4 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.17.3)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.23.5)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.6.3)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
+            "Requirement already satisfied: tokenizers<0.15,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.14.1)\n",
+            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.0)\n",
+            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (2023.6.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (4.5.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.7.22)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install transformers\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "r582IJ5IXD2N",
+        "outputId": "daabcaad-305d-4d85-d7ab-52fc0d816f72"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (0.1.99)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install sentencepiece\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "JnKRfdMEWVGO",
+        "outputId": "575d83ff-4cb3-43a0-c2b5-4b8931b0ba6c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: pytorch_lightning in /usr/local/lib/python3.10/dist-packages (2.1.1)\n",
+            "Requirement already satisfied: numpy>=1.17.2 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (1.23.5)\n",
+            "Requirement already satisfied: torch>=1.12.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (2.1.0+cu118)\n",
+            "Requirement already satisfied: tqdm>=4.57.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (4.66.1)\n",
+            "Requirement already satisfied: PyYAML>=5.4 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (6.0.1)\n",
+            "Requirement already satisfied: fsspec[http]>2021.06.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (2023.6.0)\n",
+            "Requirement already satisfied: torchmetrics>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (1.2.0)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (23.2)\n",
+            "Requirement already satisfied: typing-extensions>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (4.5.0)\n",
+            "Requirement already satisfied: lightning-utilities>=0.8.0 in /usr/local/lib/python3.10/dist-packages (from pytorch_lightning) (0.9.0)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from fsspec[http]>2021.06.0->pytorch_lightning) (2.31.0)\n",
+            "Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]>2021.06.0->pytorch_lightning) (3.8.6)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.12.0->pytorch_lightning) (3.13.1)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.12.0->pytorch_lightning) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.12.0->pytorch_lightning) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.12.0->pytorch_lightning) (3.1.2)\n",
+            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.12.0->pytorch_lightning) (2.1.0)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (23.1.0)\n",
+            "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (3.3.2)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (6.0.4)\n",
+            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (4.0.3)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (1.9.2)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (1.4.0)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch_lightning) (1.3.1)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.12.0->pytorch_lightning) (2.1.3)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (3.4)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (2023.7.22)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.12.0->pytorch_lightning) (1.3.0)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install pytorch_lightning\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "AYPbxPPyUmTX",
+        "outputId": "8ab7a0f4-caa4-434b-d52a-0e8606af8ef4"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "INFO:lightning_fabric.utilities.seed:Seed set to 100\n"
+          ]
+        }
+      ],
+      "source": [
+        "from sklearn.model_selection import train_test_split\n",
+        "\n",
+        "from transformers import T5Tokenizer, T5ForConditionalGeneration\n",
+        "\n",
+        "from transformers import AdamW\n",
+        "import pandas as pd\n",
+        "import torch\n",
+        "import pytorch_lightning as pl\n",
+        "from pytorch_lightning.callbacks import ModelCheckpoint\n",
+        "from torch.nn.utils.rnn import pad_sequence\n",
+        "# from torch.utils.data import Dataset, DataLoader, random_split, RandomSampler, SequentialSampler\n",
+        "\n",
+        "pl.seed_everything(100)\n",
+        "import warnings\n",
+        "warnings.filterwarnings(\"ignore\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2KetQ8LzU5Xw"
+      },
+      "outputs": [],
+      "source": [
+        "data = pd.read_csv(\"Conversation.csv\")\n",
+        "data.drop(columns=['Unnamed: 0'],inplace=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "XbgyKcoEWtJu",
+        "outputId": "3b0b2716-7b34-40d9-98a0-bc27d4b4f640"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "No of rows: 3725\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"No of rows:\" ,data.shape[0])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "dRgL6Pp-WxQF"
+      },
+      "outputs": [],
+      "source": [
+        "DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
+        "INPUT_MAX_LEN = 128 #input length\n",
+        "OUTPUT_MAX_LEN = 128 # output length\n",
+        "TRAIN_BATCH_SIZE = 8 # batch size of training\n",
+        "VAL_BATCH_SIZE = 2 # batch size for validation\n",
+        "EPOCHS = 5 # number of epoch"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 170,
+          "referenced_widgets": [
+            "17d569c96c5c4d5a8495a3a294cd5794",
+            "bf6a0e76a7a547ad9a1ae4ff5d41cde1",
+            "8d5456a15f2f4a1d942ffec17d2bbf3b",
+            "66df9eab44fd46158ce66301d52442ee",
+            "d95d821cdad34aefa6ef9da901b635ae",
+            "b0bfdaace6db44b18a0c1f4678602e44",
+            "2cccb4979aae4088b3b3b5ed6535fa8f",
+            "10da814e6b7b48698d92abecf1a2c8d2",
+            "76d4b0ce92f14f5086e4d2dcb4838bd9",
+            "76db35992a0148fa8f34912b140f32ad",
+            "46b8f2c5ac19472e8d1cab734c60bea6",
+            "a2a4d1c023c840eb8eecc9db984c51cf",
+            "ea89580721f246a38162273eae662afe",
+            "20b43a93655c49558787cceac269707e",
+            "63404a1a221148f19fb6b539107edea2",
+            "97aa2fa33c7e4d8780dc59a6627ec551",
+            "1bca6293972b45e4a7d48704012c794f",
+            "840cbab88ba74a4984208be560586391",
+            "73cf23dc9260414e9395e9283ebb22a0",
+            "c6a6196e392f4b28a47eeb76719a9f5e",
+            "7fa433925c7d4f2085032ef34f1ebea9",
+            "4321e66ed9164b0e8a3619497f19e600",
+            "94b74dee162747e2b74e3d49b8a6eeee",
+            "98471106a9884b92aff88d05b8b59e4b",
+            "db956786289b4934bcd8644ceeeb1629",
+            "af82522ec6c74954a36947729d267bc9",
+            "911e513226c84a289a63e6d76b731b09",
+            "7fd9b2a289ab45089ab77e089af96879",
+            "887214c42410453baeb2e258a1239966",
+            "0f67828b2fdd4ebaa7cb7a4c7b321244",
+            "8aad0bc9ed274cac874e24a3c45d2979",
+            "013396e9dae14f2bbf3e729b69a566a7",
+            "c4d7492e8ce344dc91bcadc7b65b3870"
+          ]
+        },
+        "id": "YUHIA3_PW19e",
+        "outputId": "42c5a216-116b-47e9-ee16-bf0210e12e91"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading (…)ve/main/spiece.model:   0%|          | 0.00/792k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "17d569c96c5c4d5a8495a3a294cd5794"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.39M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "a2a4d1c023c840eb8eecc9db984c51cf"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.21k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "94b74dee162747e2b74e3d49b8a6eeee"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n",
+            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+          ]
+        }
+      ],
+      "source": [
+        "MODEL_NAME = \"t5-base\"\n",
+        "tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME, model_max_length=512)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "l7NRrwnOXhv1"
+      },
+      "outputs": [],
+      "source": [
+        "text = \"Hello, how are you today?\"    # assume the text that is to be tokenized\n",
+        "\n",
+        "input_tokenize = tokenizer(\n",
+        "             text,\n",
+        "            add_special_tokens=True,        #Add Special tokens like [CLS] and [SEP]\n",
+        "            max_length=128,\n",
+        "            padding = 'max_length',         #for padding to max_length for equal sequence length\n",
+        "            truncation = True,              #truncate the text if it is greater than max_length\n",
+        "            return_attention_mask=True,     #will return attention mask\n",
+        "            return_tensors=\"pt\"             #return tensor formate\n",
+        "        )"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Ibq5SgJ5Xkr1",
+        "outputId": "cbc3b943-3d12-49d1-af59-b72184e759ff"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "input_ids:  tensor([8774,    6,  149,   33,   25,  469,   58,    1,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+            "           0,    0,    0,    0,    0,    0,    0,    0])\n",
+            "-----------------------------------------------------------------------------\n",
+            "Attention Mask:  tensor([1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+            "        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+            "        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+            "        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+            "        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+            "        0, 0, 0, 0, 0, 0, 0, 0])\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"input_ids: \", input_tokenize['input_ids'].flatten())\n",
+        "print(\"-----------------------------------------------------------------------------\")\n",
+        "print(\"Attention Mask: \", input_tokenize['attention_mask'].flatten())"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "aPrWy2YdXpsx"
+      },
+      "outputs": [],
+      "source": [
+        "class T5Dataset:\n",
+        "\n",
+        "  def __init__(self,question,answer):\n",
+        "\n",
+        "    self.question = question\n",
+        "    self.answer = answer\n",
+        "    self.tokenizer = tokenizer\n",
+        "    self.input_max_len = INPUT_MAX_LEN\n",
+        "    self.output_max_len = OUTPUT_MAX_LEN\n",
+        "\n",
+        "  def __len__(self):                      # This method retrives the number of item from the dataset\n",
+        "    return len(self.question)\n",
+        "\n",
+        "  def __getitem__(self,item):             # This method retrieves the item at the specified index item.\n",
+        "\n",
+        "    question = str(self.question[item])\n",
+        "    question = ''.join(question.split())\n",
+        "\n",
+        "    answer = str(self.answer[item])\n",
+        "    answer = ''.join(answer.split())\n",
+        "\n",
+        "    input_tokenize = self.tokenizer(\n",
+        "            question,\n",
+        "            add_special_tokens=True,\n",
+        "            max_length=self.input_max_len,\n",
+        "            padding = 'max_length',\n",
+        "            truncation = True,\n",
+        "            return_attention_mask=True,\n",
+        "            return_tensors=\"pt\"\n",
+        "        )\n",
+        "    output_tokenize = self.tokenizer(\n",
+        "            answer,\n",
+        "            add_special_tokens=True,\n",
+        "            max_length=self.output_max_len,\n",
+        "            padding = 'max_length',\n",
+        "            truncation = True,\n",
+        "            return_attention_mask=True,\n",
+        "            return_tensors=\"pt\"\n",
+        "\n",
+        "        )\n",
+        "\n",
+        "\n",
+        "    input_ids = input_tokenize[\"input_ids\"].flatten()\n",
+        "    attention_mask = input_tokenize[\"attention_mask\"].flatten()\n",
+        "    labels = output_tokenize['input_ids'].flatten()\n",
+        "\n",
+        "    out = {\n",
+        "            'question':question,\n",
+        "            'answer':answer,\n",
+        "            'input_ids': input_ids,\n",
+        "            'attention_mask':attention_mask,\n",
+        "            'target':labels\n",
+        "        }\n",
+        "\n",
+        "    return out"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "KiXUygzPXxDL"
+      },
+      "outputs": [],
+      "source": [
+        "class T5DataLoad(pl.LightningDataModule):\n",
+        "\n",
+        "    def __init__(self,df_train,df_test):\n",
+        "        super().__init__()\n",
+        "        self.df_train = df_train\n",
+        "        self.df_test = df_test\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.input_max_len = INPUT_MAX_LEN\n",
+        "        self.out_max_len = OUTPUT_MAX_LEN\n",
+        "\n",
+        "    def setup(self, stage=None):\n",
+        "\n",
+        "        self.train_data = T5Dataset(\n",
+        "            question = self.df_train.question.values,\n",
+        "            answer = self.df_train.answer.values\n",
+        "        )\n",
+        "\n",
+        "        self.valid_data = T5Dataset(\n",
+        "            question = self.df_test.question.values,\n",
+        "            answer = self.df_test.answer.values\n",
+        "        )\n",
+        "    def train_dataloader(self):\n",
+        "        return torch.utils.data.DataLoader(\n",
+        "         self.train_data,\n",
+        "         batch_size= TRAIN_BATCH_SIZE,\n",
+        "         shuffle=True,\n",
+        "         num_workers=2\n",
+        "        )\n",
+        "    def val_dataloader(self):\n",
+        "        return torch.utils.data.DataLoader(\n",
+        "        self.valid_data,\n",
+        "        batch_size= VAL_BATCH_SIZE,\n",
+        "        num_workers = 2\n",
+        "        )"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "-9nt58JwX3wr"
+      },
+      "outputs": [],
+      "source": [
+        "class T5Model(pl.LightningModule):\n",
+        "\n",
+        "    def __init__(self):\n",
+        "        super().__init__()\n",
+        "        self.model = T5ForConditionalGeneration.from_pretrained(MODEL_NAME, return_dict = True)\n",
+        "\n",
+        "\n",
+        "    def forward(self, input_ids, attention_mask, labels=None):\n",
+        "\n",
+        "        output = self.model(\n",
+        "        input_ids=input_ids,\n",
+        "        attention_mask=attention_mask,\n",
+        "        labels=labels\n",
+        "        )\n",
+        "        return output.loss, output.logits\n",
+        "\n",
+        "    def training_step(self, batch, batch_idx):\n",
+        "\n",
+        "        input_ids = batch[\"input_ids\"]\n",
+        "        attention_mask = batch[\"attention_mask\"]\n",
+        "        labels= batch[\"target\"]\n",
+        "        loss, logits = self(input_ids , attention_mask, labels)\n",
+        "\n",
+        "\n",
+        "        self.log(\"train_loss\", loss, prog_bar=True, logger=True)\n",
+        "\n",
+        "        return {'loss': loss}\n",
+        "\n",
+        "    def validation_step(self, batch, batch_idx):\n",
+        "        input_ids = batch[\"input_ids\"]\n",
+        "        attention_mask = batch[\"attention_mask\"]\n",
+        "        labels= batch[\"target\"]\n",
+        "        loss, logits = self(input_ids, attention_mask, labels)\n",
+        "\n",
+        "        self.log(\"val_loss\", loss, prog_bar=True, logger=True)\n",
+        "\n",
+        "        return {'val_loss': loss}\n",
+        "\n",
+        "    def configure_optimizers(self):\n",
+        "        return AdamW(self.parameters(), lr=0.0001)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "-SwnA1q1Z2i8",
+        "outputId": "3db69601-6f3d-438f-e472-59da7e20e944"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in links: https://download.pytorch.org/whl/cu102/torch_stable.html\n",
+            "\u001b[31mERROR: Could not find a version that satisfies the requirement torch==1.9.0+cu102 (from versions: 1.11.0, 1.11.0+cu102, 1.12.0, 1.12.0+cu102, 1.12.1, 1.12.1+cu102, 1.13.0, 1.13.1, 2.0.0, 2.0.1, 2.1.0)\u001b[0m\u001b[31m\n",
+            "\u001b[0m\u001b[31mERROR: No matching distribution found for torch==1.9.0+cu102\u001b[0m\u001b[31m\n",
+            "\u001b[0mCollecting pytorch-lightning==1.4.9\n",
+            "  Downloading pytorch_lightning-1.4.9-py3-none-any.whl (925 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m925.8/925.8 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: numpy>=1.17.2 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (1.23.5)\n",
+            "Requirement already satisfied: torch>=1.6 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (2.1.0+cu118)\n",
+            "Requirement already satisfied: future>=0.17.1 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (0.18.3)\n",
+            "Requirement already satisfied: tqdm>=4.41.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (4.66.1)\n",
+            "Requirement already satisfied: PyYAML>=5.1 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (6.0.1)\n",
+            "Requirement already satisfied: fsspec[http]!=2021.06.0,>=2021.05.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (2023.6.0)\n",
+            "Requirement already satisfied: tensorboard>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (2.14.1)\n",
+            "Requirement already satisfied: torchmetrics>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (1.2.0)\n",
+            "Collecting pyDeprecate==0.3.1 (from pytorch-lightning==1.4.9)\n",
+            "  Downloading pyDeprecate-0.3.1-py3-none-any.whl (10 kB)\n",
+            "Requirement already satisfied: packaging>=17.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (23.2)\n",
+            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.4.9) (4.5.0)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (2.31.0)\n",
+            "Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (3.8.6)\n",
+            "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (1.4.0)\n",
+            "Requirement already satisfied: grpcio>=1.48.2 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (1.59.2)\n",
+            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (2.17.3)\n",
+            "Requirement already satisfied: google-auth-oauthlib<1.1,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (1.0.0)\n",
+            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (3.5.1)\n",
+            "Requirement already satisfied: protobuf>=3.19.6 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (3.20.3)\n",
+            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (67.7.2)\n",
+            "Requirement already satisfied: six>1.9 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (1.16.0)\n",
+            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (0.7.2)\n",
+            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard>=2.2.0->pytorch-lightning==1.4.9) (3.0.1)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->pytorch-lightning==1.4.9) (3.13.1)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->pytorch-lightning==1.4.9) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->pytorch-lightning==1.4.9) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->pytorch-lightning==1.4.9) (3.1.2)\n",
+            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->pytorch-lightning==1.4.9) (2.1.0)\n",
+            "Requirement already satisfied: lightning-utilities>=0.8.0 in /usr/local/lib/python3.10/dist-packages (from torchmetrics>=0.4.0->pytorch-lightning==1.4.9) (0.9.0)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (23.1.0)\n",
+            "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (3.3.2)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (6.0.4)\n",
+            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (4.0.3)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (1.9.2)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (1.4.0)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (1.3.1)\n",
+            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (5.3.2)\n",
+            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (0.3.0)\n",
+            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (4.9)\n",
+            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<1.1,>=0.5->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (1.3.1)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (3.4)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->fsspec[http]!=2021.06.0,>=2021.05.0->pytorch-lightning==1.4.9) (2023.7.22)\n",
+            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (2.1.3)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.6->pytorch-lightning==1.4.9) (1.3.0)\n",
+            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (0.5.0)\n",
+            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard>=2.2.0->pytorch-lightning==1.4.9) (3.2.2)\n",
+            "Installing collected packages: pyDeprecate, pytorch-lightning\n",
+            "  Attempting uninstall: pytorch-lightning\n",
+            "    Found existing installation: pytorch-lightning 2.1.1\n",
+            "    Uninstalling pytorch-lightning-2.1.1:\n",
+            "      Successfully uninstalled pytorch-lightning-2.1.1\n",
+            "Successfully installed pyDeprecate-0.3.1 pytorch-lightning-1.4.9\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "pytorch_lightning"
+                ]
+              }
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "!pip install torch==1.9.0+cu102 torchvision==0.10.0+cu102 torchaudio==0.9.0+cu102 -f https://download.pytorch.org/whl/cu102/torch_stable.html\n",
+        "!pip install pytorch-lightning==1.4.9\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 372
+        },
+        "id": "ic3a_2MwX_cE",
+        "outputId": "561cc9ae-5960-4cac-b946-77bde7a7e9de"
+      },
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "TypeError",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-21-7142c2beb2c5>\u001b[0m in \u001b[0;36m<cell line: 25>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     23\u001b[0m     \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdataload\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m \u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+            "\u001b[0;32m<ipython-input-21-7142c2beb2c5>\u001b[0m in \u001b[0;36mrun\u001b[0;34m()\u001b[0m\n\u001b[1;32m     15\u001b[0m         \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"min\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     )\n\u001b[0;32m---> 17\u001b[0;31m     trainer = pl.Trainer(\n\u001b[0m\u001b[1;32m     18\u001b[0m         \u001b[0mcallbacks\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcheckpoint\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# Using a list of callbacks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m         \u001b[0mmax_epochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pytorch_lightning/utilities/argparse.py\u001b[0m in \u001b[0;36minsert_env_defaults\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     68\u001b[0m                 \u001b[0;31m# We always set to True, regardless of the default value.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0;31m# Users must pass False directly, but when passing nothing True is assumed.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m                 \u001b[0;31m# i.e. the only way to disable something that defaults to True is to use the long form:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m                 \u001b[0;31m# \"--a_default_true_arg False\" becomes False, while \"--a_default_false_arg\" becomes None,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m                 \u001b[0;31m# which then becomes True here.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mTypeError\u001b[0m: Trainer.__init__() got an unexpected keyword argument 'gpus'"
+          ]
+        }
+      ],
+      "source": [
+        "\n",
+        "def run():\n",
+        "    df_train, df_test = train_test_split(data, test_size=0.2, random_state=100)\n",
+        "    dataload = T5DataLoad(df_train, df_test)\n",
+        "    dataload.setup()\n",
+        "    device = DEVICE\n",
+        "    model = T5Model()\n",
+        "    model.to(device)\n",
+        "\n",
+        "    checkpoint = ModelCheckpoint(\n",
+        "        dirpath=\"/kaggle/working\",\n",
+        "        filename='best-model',\n",
+        "        save_top_k=2,\n",
+        "        verbose=True,\n",
+        "        monitor=\"val_loss\",\n",
+        "        mode=\"min\"\n",
+        "    )\n",
+        "    trainer = pl.Trainer(\n",
+        "        callbacks=[checkpoint],  # Using a list of callbacks\n",
+        "        max_epochs=1,\n",
+        "        gpus=1,\n",
+        "        accelerator=\"gpu\"\n",
+        "    )\n",
+        "    trainer.fit(model, dataload)\n",
+        "\n",
+        "run()\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1AvdzfihYJhU"
+      },
+      "outputs": [],
+      "source": [
+        "train_model = T5Model.load_from_checkpoint('/kaggle/working/best-model.ckpt')\n",
+        "train_model.freeze()\n",
+        "\n",
+        "def generate_question(question):\n",
+        "\n",
+        "    inputs_encoding =  tokenizer(\n",
+        "        question,\n",
+        "        add_special_tokens=True,\n",
+        "        max_length= INPUT_MAX_LEN,\n",
+        "        padding = 'max_length',\n",
+        "        truncation='only_first',\n",
+        "        return_attention_mask=True,\n",
+        "        return_tensors=\"pt\"\n",
+        "        )\n",
+        "\n",
+        "\n",
+        "    generate_ids = train_model.model.generate(\n",
+        "        input_ids = inputs_encoding[\"input_ids\"],\n",
+        "        attention_mask = inputs_encoding[\"attention_mask\"],\n",
+        "        max_length = INPUT_MAX_LEN,\n",
+        "        num_beams = 4,\n",
+        "        num_return_sequences = 1,\n",
+        "        no_repeat_ngram_size=2,\n",
+        "        early_stopping=True,\n",
+        "        )\n",
+        "\n",
+        "    preds = [\n",
+        "        tokenizer.decode(gen_id,\n",
+        "        skip_special_tokens=True,\n",
+        "        clean_up_tokenization_spaces=True)\n",
+        "        for gen_id in generate_ids\n",
+        "    ]\n",
+        "\n",
+        "    return \"\".join(preds)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "CJUECi2EaUp5"
+      },
+      "outputs": [],
+      "source": [
+        "ques = \"hi, how are you doing?\"\n",
+        "print(\"Ques: \",ques)\n",
+        "print(\"BOT: \",generate_question(ques))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "MUXSpra-rlm5"
+      },
+      "outputs": [],
+      "source": [
+        "ques = \"how's it going?\"\n",
+        "print(\"Ques: \",ques)\n",
+        "print(\"BOT: \",generate_question(ques))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "JN6rp0SKrr2g"
+      },
+      "outputs": [],
+      "source": [
+        "ques = \"i heard that it's going to be warm this weekend.\"\n",
+        "print(\"Ques: \",ques)\n",
+        "print(\"BOT: \",generate_question(ques))"
+      ]
+    }
+  ],
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