New optimizers are failing with these two tutorials.

Switch to legacy optimizers so these still work for TF2.11

PiperOrigin-RevId: 484547539

Author: MarkDaoust

site/en/guide/migrate/multi_worker_cpu_gpu_training.ipynb

@@ -369,7 +369,7 @@
         "\n",
         "with strategy.scope():\n",
         "  model = tf.keras.models.Sequential([tf.keras.layers.Dense(1)])\n",
-        "  optimizer = tf.keras.optimizers.Adagrad(learning_rate=0.05)\n",
+        "  optimizer = tf.keras.optimizers.legacy.Adagrad(learning_rate=0.05)\n",
         "  model.compile(optimizer, \"mse\")\n",
         "\n",
         "model.fit(dataset, epochs=5, steps_per_epoch=10)"
@@ -464,6 +464,7 @@
     "colab": {
       "collapsed_sections": [],
       "name": "multi_worker_cpu_gpu_training.ipynb",
+      "provenance": [],
       "toc_visible": true
     },
     "kernelspec": {

site/en/tutorials/distribute/parameter_server_training.ipynb

@@ -438,7 +438,7 @@
         "with strategy.scope():\n",
         "  model = tf.keras.models.Sequential([tf.keras.layers.Dense(10)])\n",
         "\n",
-        "  model.compile(tf.keras.optimizers.SGD(), loss=\"mse\", steps_per_execution=10)"
+        "  model.compile(tf.keras.optimizers.legacy.SGD(), loss=\"mse\", steps_per_execution=10)"
       ]
     },
     {
@@ -660,7 +660,7 @@
         "  dense_output = tf.keras.layers.Dense(units=1, activation=\"sigmoid\")(emb_output)\n",
         "  model = tf.keras.Model({\"features\": model_input}, dense_output)\n",
         "\n",
-        "  optimizer = tf.keras.optimizers.RMSprop(learning_rate=0.1)\n",
+        "  optimizer = tf.keras.optimizers.legacy.RMSprop(learning_rate=0.1)\n",
         "  accuracy = tf.keras.metrics.Accuracy()"
       ]
     },