Replace unicode escaped characters in ipynb files

PiperOrigin-RevId: 854213756

Author: AleksMat

notebooks/t5-trivia.ipynb

@@ -7,7 +7,7 @@
       },
       "source": [
         "\n",
-        "\u003ca href=\"https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb\" target=\"_parent\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e"
+        "<a href=\"https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -55,7 +55,7 @@
         "## _Or: What does T5 know?_\n",
         "\n",
         "*The following tutorial guides you through the process of fine-tuning a pre-trained T5 model, evaluating its accuracy, and using it for prediction,\n",
-        "all on a free Google Cloud TPU \u003ca href=\"https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb\" target=\"_parent\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e.*\n",
+        "all on a free Google Cloud TPU <a href=\"https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/main/notebooks/t5-trivia.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>.*\n",
         "\n",
         "### Background\n",
         "\n",
@@ -102,7 +102,7 @@
         "id": "eDeE_yVuHMYg"
       },
       "source": [
-        "\u003ch3\u003e\u003ca href=\"https://cloud.google.com/tpu/\"\u003e\u003cimg valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/tpu-hexagon.png\" width=\"50\"\u003e\u003c/a\u003e  \u0026nbsp;\u0026nbsp;Train on TPU\u003c/h3\u003e\n",
+        "<h3><a href=\"https://cloud.google.com/tpu/\"><img valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/tpu-hexagon.png\" width=\"50\"></a>  &nbsp;&nbsp;Train on TPU</h3>\n",
         "\n",
         "\n",
         "\n",
@@ -253,7 +253,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "I1206 00:11:00.169766 248738 \u003cipython-input-3-45e03d923fbf\u003e:51] Loading NQ from cache.\n"
+            "I1206 00:11:00.169766 248738 <ipython-input-3-45e03d923fbf>:51] Loading NQ from cache.\n"
           ]
         }
       ],
@@ -304,7 +304,7 @@
         "      elif \"document_text\" in ex:\n",
         "        tokens = ex[\"document_text\"].split(\" \")\n",
         "      answer = extract_answer(tokens, answer_span)\n",
-        "      # Write this line as \u003cquestion\u003e\\t\u003canswer\u003e\n",
+        "      # Write this line as <question>\\t<answer>\n",
         "      outfile.write(\"%s\\t%s\\n\" % (question, answer))\n",
         "      count += 1\n",
         "      tf.logging.log_every_n(\n",
@@ -378,7 +378,7 @@
         "\n",
         "  # Load lines from the text file as examples.\n",
         "  ds = tf.data.TextLineDataset(nq_tsv_path[split])\n",
-        "  # Split each \"\u003cquestion\u003e\\t\u003canswer\u003e\" example into (question, answer) tuple.\n",
+        "  # Split each \"<question>\\t<answer>\" example into (question, answer) tuple.\n",
         "  ds = ds.map(\n",
         "      functools.partial(tf.io.decode_csv, record_defaults=[\"\", \"\"],\n",
         "                        field_delim=\"\\t\", use_quote_delim=False),\n",
@@ -417,7 +417,7 @@
         "    return text\n",
         "\n",
         "  def to_inputs_and_targets(ex):\n",
-        "    \"\"\"Map {\"question\": ..., \"answer\": ...}-\u003e{\"inputs\": ..., \"targets\": ...}.\"\"\"\n",
+        "    \"\"\"Map {\"question\": ..., \"answer\": ...}->{\"inputs\": ..., \"targets\": ...}.\"\"\"\n",
         "    return {\n",
         "        \"inputs\":\n",
         "             tf.strings.join(\n",
@@ -889,7 +889,7 @@
         "\n",
         "Please see our [paper on closed-book QA](https://arxiv.org/abs/2002.08910) where achieved even better results.\n",
         "\n",
-        "\u003cimg src=\"https://storage.googleapis.com/t5-data/assets/t5_trivia_expected.png\"\u003e"
+        "<img src=\"https://storage.googleapis.com/t5-data/assets/t5_trivia_expected.png\">"
       ]
     },
     {
@@ -954,7 +954,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "\u003c== Random predictions for triviaqa_context_free using checkpoint 1100000 ==\u003e\n",
+            "<== Random predictions for triviaqa_context_free using checkpoint 1100000 ==>\n",
             "\n",
             "Input: trivia question: jackpot counter, ghost drop and drop zone are all terms used in which uk television game show?\n",
             "Target: tipping point\n",
@@ -1006,7 +1006,7 @@
             "Prediction: scooby-doo\n",
             "Counted as Correct? False\n",
             "\n",
-            "\u003c== Random predictions for nq_context_free using checkpoint 1100000 ==\u003e\n",
+            "<== Random predictions for nq_context_free using checkpoint 1100000 ==>\n",
             "\n",
             "Input: trivia question: who is known as the super fast boy in the series the icredible?\n",
             "Target: dashiell robert parr/dash\n",
@@ -1093,7 +1093,7 @@
         "                      tf.compat.as_text(ex[\"targets_pretokenized\"]),\n",
         "                      pred.strip()))\n",
         "\n",
-        "  print(\"\u003c== Random predictions for %s using checkpoint %s ==\u003e\\n\" %\n",
+        "  print(\"<== Random predictions for %s using checkpoint %s ==>\\n\" %\n",
         "        (task_name, \n",
         "         _prediction_file_to_ckpt(latest_prediction_file)))\n",
         "\n",