Updating cuda version and cupy version

- latest Colab environment has changed and cuda and cupy versions cause
  issues, that are reported from learners
- Sebastian has research the issue and updated the notebook

hw_openqa.ipynb

@@ -158,7 +158,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install torch==1.10.0\n",
+    "!pip install torch==1.10.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n",
     "\n",
     "!pip install ujson\n",
     "\n",
@@ -195,7 +195,8 @@
     "import torch\n",
     "\n",
     "if torch.cuda.is_available():\n",
-    "    !pip install cupy-cuda111"
+    "    !pip uninstall cupy-cuda11x -y\n",
+    "    !pip install cupy-cuda113"
    ]
   },
   {
@@ -404,13 +405,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "6LWz4f-3Yres",
-    "outputId": "11bb2cc3-140e-46d0-d04f-a35f74c97e12"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
@@ -419,8 +414,7 @@
     "\n",
     "from colbert.infra import Run, RunConfig, ColBERTConfig\n",
     "from colbert.data import Collection\n",
-    "from colbert.searcher import Searcher\n",
-    "from utility.utils.dpr import has_answer, DPR_normalize"
+    "from colbert.searcher import Searcher"
    ]
   },
   {
@@ -1637,6 +1631,15 @@
     "For more rigorous evaluations of the retriever alone, we can use Sucess@`k` defined relative to the SQuAD passages and answers. We say that we have a \"success\" if a passage in the top `k` retrieved passages contains any of the answers substrings, and Sucess@`k` is the percentage of such success cases. This is very heuristic (perhaps the answer string happens to occur somewhere in a completely irrelevant passage), but it can still be good guidance."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from utility.utils.dpr import has_answer, DPR_normalize"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -2170,21 +2173,6 @@
     "test_evaluator(evaluate_few_shot_open_qa)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "pXNI9BRNYre3",
-    "outputId": "2e428199-d5f7-4346-a80f-7a6934366efe"
-   },
-   "outputs": [],
-   "source": [
-    "\n"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -2603,11 +2591,8 @@
    "provenance": [],
    "toc_visible": true
   },
-  "interpreter": {
-   "hash": "a99ac6d2deb03d0b7ced3594556c328848678d7cea021ae1b9990e15d3ad5c49"
-  },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "nlu",
    "language": "python",
    "name": "python3"
   },
@@ -2621,7 +2606,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.16"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "81ef301a63437b26d6f879bc64646dce7fed7674109198cc71f09ca02787000d"
+   }
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {