Add validation_steps to fix Colab.

PiperOrigin-RevId: 324701287

Author: MarkDaoust

site/en/guide/tpu.ipynb

@@ -354,14 +354,16 @@
         "\n",
         "batch_size = 200\n",
         "steps_per_epoch = 60000 // batch_size\n",
+        "validation_steps = 10000 // batch_size\n",
         "\n",
         "train_dataset = get_dataset(batch_size, is_training=True)\n",
         "test_dataset = get_dataset(batch_size, is_training=False)\n",
         "\n",
         "model.fit(train_dataset,\n",
         "          epochs=5,\n",
         "          steps_per_epoch=steps_per_epoch,\n",
-        "          validation_data=test_dataset)"
+        "          validation_data=test_dataset, \n",
+        "          validation_steps=validation_steps)"
       ]
     },
     {
@@ -371,7 +373,7 @@
         "id": "8hSGBIYtUugJ"
       },
       "source": [
-        "To reduce python overhead, and maximize the performance of your TPU, try out the **experimental** `experimental_steps_per_execution` argument to `Model.compile`. Here it approximately **doubles** the throughput:"
+        "To reduce python overhead, and maximize the performance of your TPU, try out the **experimental** `experimental_steps_per_execution` argument to `Model.compile`. Here it increases throughput by about 50%:"
       ]
     },
     {
@@ -395,7 +397,8 @@
         "model.fit(train_dataset,\n",
         "          epochs=5,\n",
         "          steps_per_epoch=steps_per_epoch,\n",
-        "          validation_data=test_dataset)"
+        "          validation_data=test_dataset,\n",
+        "          validation_steps=validation_steps)"
       ]
     },
     {