Merge pull request #2129 from jancervenka:patch-1

PiperOrigin-RevId: 483313036

Author: copybara-github

site/en/guide/core/optimizers_core.ipynb

@@ -13,6 +13,7 @@
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
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         "id": "AwOEIRJC6Une"
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       "outputs": [],
@@ -343,7 +344,7 @@
         "\n",
         "Gradient descent with momentum not only uses the gradient to update a variable but also involves the change in position of a variable based on its previous update. The momentum parameter determines the level of influence the update at timestep $t-1$ has on the update at timestep $t$. Accumulating momentum helps to move variables past plataeu regions faster than basic gradient descent. The momentum update rule is as follows:\n",
         "\n",
-        "$$\\Delta_x^{[t]} = lr \\cdot L^\\prime(x^{[t]}) + p \\cdot \\Delta_x^{[t-1]}$$\n",
+        "$$\\Delta_x^{[t]} = lr \\cdot L^\\prime(x^{[t-1]}) + p \\cdot \\Delta_x^{[t-1]}$$\n",
         "\n",
         "$$x^{[t]} = x^{[t-1]} - \\Delta_x^{[t]}$$\n",
         "\n",
@@ -591,21 +592,16 @@
         "This notebook introduced the basics of writing and comparing optimizers with the [TensorFlow Core APIs](https://www.tensorflow.org/guide/core). Although prebuilt optimizers like Adam are generalizable, they may not always be the best choice for every model or dataset. Having fine-grained control over the optimization process can help streamline ML training workflows and improve overall performance. Refer to the following documentation for more examples of custom optimizers:\n",
         "\n",
         "*   This Adam optimizer is used in the [Multilayer perceptrons](https://www.tensorflow.org/guide/core/mlp_core) tutorial and the [Distributed training]()\n",
-        "*   [Model Garden](https://blog.tensorflow.org/2020/03/introducing-model-garden-for-tensorflow-2.html) has a variety of [custom optimizers](https://github.com/tensorflow/models/tree/master/official/modeling/optimization) written with the Core APIs.\n",
-        "\n",
-        "\n",
-        "\n"
+        "*   [Model Garden](https://blog.tensorflow.org/2020/03/introducing-model-garden-for-tensorflow-2.html) has a variety of [custom optimizers](https://github.com/tensorflow/models/tree/master/official/modeling/optimization) written with the Core APIs.\n"
       ]
     }
   ],
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       "name": "optimizers_core.ipynb",
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-    "gpuClass": "standard",
     "kernelspec": {
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