Replace unicode escaped characters in ipynb files

AleksMat · copybara-github · commit 60c51e7a4b34 · 2026-01-14T03:10:12.000-08:00
PiperOrigin-RevId: 856131304
diff --git a/site/en/guide/mixed_precision.ipynb b/site/en/guide/mixed_precision.ipynb
@@ -121,8 +121,8 @@
         "While mixed precision will run on most hardware, it will only speed up models on recent NVIDIA GPUs, Cloud TPUs and recent Intel CPUs. NVIDIA GPUs support using a mix of float16 and float32, while TPUs and Intel CPUs support a mix of bfloat16 and float32.\n",
         "\n",
         "Among NVIDIA GPUs, those with compute capability 7.0 or higher will see the greatest performance benefit from mixed precision because they have special hardware units, called Tensor Cores, to accelerate float16 matrix multiplications and convolutions. Older GPUs offer no math performance benefit for using mixed precision, however memory and bandwidth savings can enable some speedups. You can look up the compute capability for your GPU at NVIDIA's [CUDA GPU web page](https://developer.nvidia.com/cuda-gpus). Examples of GPUs that will benefit most from mixed precision include RTX GPUs, the V100, and the A100.\n",
-       "\n",
-       "Among Intel CPUs, starting with the 4th Gen Intel Xeon Processors (code name Sapphire Rapids), will see the greatest performance benefit from mixed precision as they can accelerate bfloat16 computations using AMX instructions (requires Tensorflow 2.12 or later)."
+        "\n",
+        "Among Intel CPUs, starting with the 4th Gen Intel Xeon Processors (code name Sapphire Rapids), will see the greatest performance benefit from mixed precision as they can accelerate bfloat16 computations using AMX instructions (requires Tensorflow 2.12 or later)."
       ]
     },
     {
diff --git a/site/en/hub/tutorials/biggan_generation_with_tf_hub.ipynb b/site/en/hub/tutorials/biggan_generation_with_tf_hub.ipynb
@@ -344,7 +344,7 @@
         "num_samples = 10 #@param {type:\"slider\", min:1, max:20, step:1}\n",
         "truncation = 0.4 #@param {type:\"slider\", min:0.02, max:1, step:0.02}\n",
         "noise_seed = 0 #@param {type:\"slider\", min:0, max:100, step:1}\n",
-        "category = \"933) cheeseburger\"\n", 
+        "category = \"933) cheeseburger\"\n",
         "\n",
         "z = truncated_z_sample(num_samples, truncation, noise_seed)\n",
         "y = int(category.split(')')[0])\n",
diff --git a/site/en/r1/guide/keras.ipynb b/site/en/r1/guide/keras.ipynb
@@ -1211,7 +1211,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "keras.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/distribute/input.ipynb b/site/en/tutorials/distribute/input.ipynb
@@ -1096,7 +1096,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "input.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/distribute/multi_worker_with_ctl.ipynb b/site/en/tutorials/distribute/multi_worker_with_ctl.ipynb
@@ -1088,7 +1088,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "multi_worker_with_ctl.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/distribute/multi_worker_with_estimator.ipynb b/site/en/tutorials/distribute/multi_worker_with_estimator.ipynb
@@ -351,7 +351,7 @@
         "Tce3stUlHN0L"
       ],
       "name": "multi_worker_with_estimator.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/distribute/multi_worker_with_keras.ipynb b/site/en/tutorials/distribute/multi_worker_with_keras.ipynb
@@ -1285,7 +1285,7 @@
   "metadata": {
     "colab": {
       "name": "multi_worker_with_keras.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/distribute/parameter_server_training.ipynb b/site/en/tutorials/distribute/parameter_server_training.ipynb
@@ -1383,7 +1383,7 @@
     "accelerator": "GPU",
     "colab": {
       "name": "parameter_server_training.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/estimator/keras_model_to_estimator.ipynb b/site/en/tutorials/estimator/keras_model_to_estimator.ipynb
@@ -272,7 +272,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "keras_model_to_estimator.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/estimator/linear.ipynb b/site/en/tutorials/estimator/linear.ipynb
@@ -600,7 +600,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "linear.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/generative/cyclegan.ipynb b/site/en/tutorials/generative/cyclegan.ipynb
@@ -830,7 +830,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "cyclegan.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/generative/pix2pix.ipynb b/site/en/tutorials/generative/pix2pix.ipynb
@@ -1301,7 +1301,7 @@
     "accelerator": "GPU",
     "colab": {
       "name": "pix2pix.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/generative/style_transfer.ipynb b/site/en/tutorials/generative/style_transfer.ipynb
@@ -1132,7 +1132,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "style_transfer.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/images/transfer_learning_with_hub.ipynb b/site/en/tutorials/images/transfer_learning_with_hub.ipynb
@@ -924,7 +924,7 @@
         "W_tvPdyfA-BL"
       ],
       "name": "transfer_learning_with_hub.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/site/en/tutorials/load_data/tfrecord.ipynb b/site/en/tutorials/load_data/tfrecord.ipynb
@@ -372,7 +372,6 @@
         "example_observation = [False, 4, b'goat', 0.9876]\n",
         "serialized_example = serialize_example(*example_observation)\n",
         "serialized_example"
-
       ]
     },
     {
diff --git a/site/en/tutorials/video/transfer_learning_with_movinet.ipynb b/site/en/tutorials/video/transfer_learning_with_movinet.ipynb
@@ -813,7 +813,7 @@
     "accelerator": "GPU",
     "colab": {
       "name": "transfer_learning_with_movinet.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/tools/templates/notebook.ipynb b/tools/templates/notebook.ipynb
@@ -283,7 +283,7 @@
         "Tce3stUlHN0L"
       ],
       "name": "notebook.ipynb",
-            "toc_visible": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
diff --git a/tools/tensorflow_docs/tools/nbfmt/__main__.py b/tools/tensorflow_docs/tools/nbfmt/__main__.py
@@ -45,7 +45,8 @@
 OSS = True
 
 flags.DEFINE_integer(
-    "indent", 2, "Indention level for pretty-printed JSON.", lower_bound=0)
+    "indent", 2, "Indentation level for pretty-printed JSON.", lower_bound=0
+)
 flags.DEFINE_bool("oss", None, "Use OSS formatting.")
 flags.DEFINE_bool("remove_outputs", False,
                   "Remove output cells from the notebook")
@@ -75,12 +76,6 @@ def clean_notebook(data: Dict[str, Any], nb_source: str, filepath: pathlib.Path,
 
   nbjson = json.dumps(data, sort_keys=True, ensure_ascii=False, indent=indent)
 
-  if not OSS:
-    # Serialization differences in environments.
-    str_replaces = {"<": r"\u003c", ">": r"\u003e", "&": r"\u0026"}
-    for str_from, str_to in str_replaces.items():
-      nbjson = nbjson.replace(str_from, str_to)
-
   return (nbjson + "\n").encode("utf-8")
 
 

Original file line number	Diff line number	Diff line change
`@@ -121,8 +121,8 @@`
`121`	`121`	`"While mixed precision will run on most hardware, it will only speed up models on recent NVIDIA GPUs, Cloud TPUs and recent Intel CPUs. NVIDIA GPUs support using a mix of float16 and float32, while TPUs and Intel CPUs support a mix of bfloat16 and float32.\n",`
`122`	`122`	`"\n",`
`123`	`123`	"Among NVIDIA GPUs, those with compute capability 7.0 or higher will see the greatest performance benefit from mixed precision because they have special hardware units, called Tensor Cores, to accelerate float16 matrix multiplications and convolutions. Older GPUs offer no math performance benefit for using mixed precision, however memory and bandwidth savings can enable some speedups. You can look up the compute capability for your GPU at NVIDIA's [CUDA GPU web page](https://developer.nvidia.com/cuda-gpus). Examples of GPUs that will benefit most from mixed precision include RTX GPUs, the V100, and the A100.\n",
`124`		`- "\n",`
`125`		`- "Among Intel CPUs, starting with the 4th Gen Intel Xeon Processors (code name Sapphire Rapids), will see the greatest performance benefit from mixed precision as they can accelerate bfloat16 computations using AMX instructions (requires Tensorflow 2.12 or later)."`
	`124`	`+ "\n",`
	`125`	`+ "Among Intel CPUs, starting with the 4th Gen Intel Xeon Processors (code name Sapphire Rapids), will see the greatest performance benefit from mixed precision as they can accelerate bfloat16 computations using AMX instructions (requires Tensorflow 2.12 or later)."`
`126`	`126`	`]`
`127`	`127`	`},`
`128`	`128`	`{`