Fix small typo

PiperOrigin-RevId: 574223535

site/en/tutorials/distribute/custom_training.ipynb

@@ -364,7 +364,7 @@
         "\n",
         "  * Input batches shorter than `GLOBAL_BATCH_SIZE` create unpleasant corner cases in several places. In practice, it often works best to avoid them by allowing batches to span epoch boundaries using `Dataset.repeat().batch()` and defining approximate epochs by step counts, not dataset ends. Alternatively, `Dataset.batch(drop_remainder=True)` maintains the notion of epoch but drops the last few examples.\n",
         "\n",
-        "  For illustration, this example goes the harder route and allows short batches, so that each training epoch contains each trainig example exactly once.\n",
+        "  For illustration, this example goes the harder route and allows short batches, so that each training epoch contains each training example exactly once.\n",
         "  \n",
         "  Which denominator should be used by `tf.nn.compute_average_loss()`?\n",
         "\n",