Merge pull request #1990 from MaoXianXin:typo_fix

PiperOrigin-RevId: 420965444

Author: copybara-github

site/en/guide/checkpoint.ipynb

@@ -683,7 +683,6 @@
     "colab": {
       "collapsed_sections": [],
       "name": "checkpoint.ipynb",
-      "provenance": [],
       "toc_visible": true
     },
     "kernelspec": {

site/en/r1/tutorials/images/transfer_learning.ipynb

@@ -547,7 +547,7 @@
         "\n",
         "# Freeze all the layers before the `fine_tune_at` layer\n",
         "for layer in base_model.layers[:fine_tune_at]:\n",
-        "  layer.trainable =  False"
+        "  layer.trainable = False"
       ]
     },
     {

site/en/tutorials/images/data_augmentation.ipynb

@@ -937,7 +937,7 @@
       "outputs": [],
       "source": [
         "cropped = tf.image.central_crop(image, central_fraction=0.5)\n",
-        "visualize(image,cropped)"
+        "visualize(image, cropped)"
       ]
     },
     {
@@ -989,7 +989,7 @@
         "Note: `seed` is a `Tensor` of shape `(2,)`  whose values are any integers.\n",
         "\n",
         "In the following sections, you will:\n",
-        "1.   Go over examples of using random image operations to transform an image; and\n",
+        "1.   Go over examples of using random image operations to transform an image.\n",
         "2.   Demonstrate how to apply random transformations to a training dataset."
       ]
     },
@@ -1174,7 +1174,7 @@
       },
       "outputs": [],
       "source": [
-        "# Create a `Counter` object and `Dataset.zip` it together with the trainining set.\n",
+        "# Create a `Counter` object and `Dataset.zip` it together with the training set.\n",
         "counter = tf.data.experimental.Counter()\n",
         "train_ds = tf.data.Dataset.zip((train_datasets, (counter, counter)))"
       ]

site/en/tutorials/images/transfer_learning.ipynb

@@ -839,7 +839,7 @@
         "\n",
         "# Freeze all the layers before the `fine_tune_at` layer\n",
         "for layer in base_model.layers[:fine_tune_at]:\n",
-        "  layer.trainable =  False"
+        "  layer.trainable = False"
       ]
     },
     {

site/en/tutorials/keras/regression.ipynb

@@ -768,7 +768,7 @@
       },
       "outputs": [],
       "source": [
-        "plot_horsepower(x,y)"
+        "plot_horsepower(x, y)"
       ]
     },
     {