Updated with configurable sep, and prefix, and in-order questions

Squad_V1_Question_Generation.ipynb

@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -52,47 +52,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Requirement already satisfied: datasets in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (2.9.0)\n",
-      "Requirement already satisfied: huggingface_hub in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (0.12.0)\n",
-      "Requirement already satisfied: requests>=2.19.0 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (2.28.2)\n",
-      "Requirement already satisfied: fsspec[http]>=2021.11.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (2023.1.0)\n",
-      "Requirement already satisfied: pandas in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (1.5.3)\n",
-      "Requirement already satisfied: dill<0.3.7 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (0.3.6)\n",
-      "Requirement already satisfied: tqdm>=4.62.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (4.64.1)\n",
-      "Requirement already satisfied: xxhash in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (3.2.0)\n",
-      "Requirement already satisfied: aiohttp in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (3.8.3)\n",
-      "Requirement already satisfied: packaging in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (23.0)\n",
-      "Requirement already satisfied: responses<0.19 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (0.18.0)\n",
-      "Requirement already satisfied: multiprocess in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (0.70.14)\n",
-      "Requirement already satisfied: numpy>=1.17 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (1.24.1)\n",
-      "Requirement already satisfied: pyyaml>=5.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (6.0)\n",
-      "Requirement already satisfied: pyarrow>=6.0.0 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from datasets) (11.0.0)\n",
-      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from huggingface_hub) (4.4.0)\n",
-      "Requirement already satisfied: filelock in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from huggingface_hub) (3.9.0)\n",
-      "Requirement already satisfied: multidict<7.0,>=4.5 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (6.0.4)\n",
-      "Requirement already satisfied: frozenlist>=1.1.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (1.3.3)\n",
-      "Requirement already satisfied: yarl<2.0,>=1.0 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (1.8.2)\n",
-      "Requirement already satisfied: aiosignal>=1.1.2 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (1.3.1)\n",
-      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (2.1.1)\n",
-      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (4.0.2)\n",
-      "Requirement already satisfied: attrs>=17.3.0 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from aiohttp->datasets) (22.2.0)\n",
-      "Requirement already satisfied: idna<4,>=2.5 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from requests>=2.19.0->datasets) (3.4)\n",
-      "Requirement already satisfied: certifi>=2017.4.17 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from requests>=2.19.0->datasets) (2022.12.7)\n",
-      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from requests>=2.19.0->datasets) (1.26.14)\n",
-      "Requirement already satisfied: pytz>=2020.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from pandas->datasets) (2022.7.1)\n",
-      "Requirement already satisfied: python-dateutil>=2.8.1 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from pandas->datasets) (2.8.2)\n",
-      "Requirement already satisfied: six>=1.5 in /opt/homebrew/Caskroom/miniconda/base/envs/flan-t5-e2e-qg/lib/python3.10/site-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n",
       "Note: you may need to restart the kernel to use updated packages.\n"
      ]
     }
    ],
    "source": [
-    "%pip install datasets huggingface_hub"
+    "%pip install --quiet datasets huggingface_hub"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "id": "otv5EWHoSJfB"
    },
@@ -115,7 +85,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -172,6 +142,165 @@
     "> - You need to [download the file here](https://www.simoninithomas.com/hfdataset/squad_modified_for_t5_qg.zip), unzip it and upload it in the next cell."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "57095c18c96f443797438d63995225ef",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading builder script:   0%|          | 0.00/5.27k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e29c5b6b6b044841afaaf8eafb8fe97f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading metadata:   0%|          | 0.00/2.36k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "055b42d0c8884fd29d24c34139b4bc26",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading readme:   0%|          | 0.00/7.67k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading and preparing dataset squad/plain_text to /Users/derekthomas/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453...\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9966d2b8b1d443eebf126a6b76764da4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading data files:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9d97ede01c8d4f5d9cef4a9f8cd07768",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Extracting data files:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Generating train split:   0%|          | 0/87599 [00:00<?, ? examples/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "205353d5f2f94483ae0f20bbc069a919",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Generating validation split:   0%|          | 0/10570 [00:00<?, ? examples/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset squad downloaded and prepared to /Users/derekthomas/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453. Subsequent calls will reuse this data.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1c716c7a59bf40b9a836cb342e314457",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "raw_dataset = load_dataset('squad')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Dataset({\n",
+       "    features: ['id', 'title', 'context', 'question', 'answers'],\n",
+       "    num_rows: 87599\n",
+       "})"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_dataset['train']"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 5,
@@ -680,7 +809,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.10.8"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

squad_modified_for_t5_qg.py

@@ -67,6 +67,8 @@ class SquadConfig(datasets.BuilderConfig):
 class Squad(datasets.GeneratorBasedBuilder):
     """SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
 
+    CONTEXT_PREFIX = 'gq: '
+    QUESTIONS_SEP = ' Question: '
     BUILDER_CONFIGS = [
         SquadConfig(
                 name="plain_text",
@@ -102,6 +104,7 @@ class Squad(datasets.GeneratorBasedBuilder):
             datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
             ]
 
+
     def _generate_examples(self, filepath):
         """This function returns the examples in the raw (text) form."""
         logger.info("generating examples from = %s", filepath)
@@ -110,10 +113,18 @@ class Squad(datasets.GeneratorBasedBuilder):
             squad = json.load(f)
             for article in squad["data"]:
                 for paragraph in article["paragraphs"]:
-                    source_text = f"generate questions: {paragraph['context'].strip()}"
-                    questions = [qas['question'].strip() for qas in paragraph['qas']]
-                    target_text = " {sep_token} ".join(questions)
-                    target_text = f"{target_text}"
+                    source_text = self.CONTEXT_PREFIX + paragraph['context'].strip()
+
+                    # Get questions in order
+                    qas = []
+                    for qa in paragraph['qas']:
+                        earliest_answer_start = min([answer['answer_start'] for answer in qa['answers']])
+                        question = qa['question'].strip()
+                        qas.append((earliest_answer_start, question))
+                    sorted_qas = sorted(qas, key=lambda x: x[0])
+                    only_qs = [qa[1] for qa in sorted_qas]
+                    target_text = self.QUESTIONS_SEP + self.QUESTIONS_SEP.join(only_qs)
+                    target_text = target_text.strip()
                     yield key, {
                         "context": source_text,
                         "questions": target_text}