Allow clu.data.dataset_iterator.DatasetIterator in addition to tf.dat…

…a.Iterator

PiperOrigin-RevId: 615907993

t5x/checkpoints.py

@@ -2015,7 +2015,11 @@ class DatasetCheckpointHandler(ocp.CheckpointHandler):
   def __init__(self, checkpoint_filename: str):
     self._checkpoint_filename = checkpoint_filename
 
-  def save(self, directory: epath.Path, item: tf.data.Iterator):
+  def save(
+      self,
+      directory: epath.Path,
+      item: Union[tf.data.Iterator, clu.data.dataset_iterator.DatasetIterator],
+  ):
     """Saves the given item.
 
     Args:
@@ -2025,13 +2029,20 @@ def save(self, directory: epath.Path, item: tf.data.Iterator):
     if jax.process_count() > 1:
       directory /= f'process_{jax.process_index()}-of-{jax.process_count()}'
       directory.mkdir(parents=False, exist_ok=False)
-    ckpt = tf.train.Checkpoint(ds=item)
-    ckpt.write(os.fspath(directory / self._checkpoint_filename))
+    if isinstance(item, tf.data.Iterator):
+      ckpt = tf.train.Checkpoint(ds=item)
+      ckpt.write(os.fspath(directory / self._checkpoint_filename))
+    elif isinstance(item, clu.data.dataset_iterator.DatasetIterator):
+      item.save(os.fspath(directory / self._checkpoint_filename))
     multihost_utils.sync_global_devices('DatasetCheckpointHandler:save')
 
   def restore(
-      self, directory: epath.Path, item: Optional[tf.data.Iterator] = None
-  ) -> tf.data.Iterator:
+      self,
+      directory: epath.Path,
+      item: Optional[
+          Union[tf.data.Iterator, clu.data.dataset_iterator.DatasetIterator]
+      ] = None,
+  ) -> Union[tf.data.Iterator, clu.data.dataset_iterator.DatasetIterator]:
     """Restores the given item.
 
     Args:
@@ -2045,10 +2056,13 @@ def restore(
       raise ValueError('Must provide item to restore')
     if jax.process_count() > 1:
       directory /= f'process_{jax.process_index()}-of-{jax.process_count()}'
-    ckpt = tf.train.Checkpoint(ds=item)
-    ckpt.read(
-        os.fspath(directory / self._checkpoint_filename)
-    ).assert_consumed()
+    if isinstance(item, tf.data.Iterator):
+      ckpt = tf.train.Checkpoint(ds=item)
+      ckpt.read(
+          os.fspath(directory / self._checkpoint_filename)
+      ).assert_consumed()
+    elif isinstance(item, clu.data.dataset_iterator.DatasetIterator):
+      item.load(os.fspath(directory / self._checkpoint_filename))
     return item
 
   def structure(self, directory: epath.Path) -> Any:
@@ -2259,7 +2273,9 @@ def __init__(
       directory: str,
       train_state: train_state_lib.TrainState,
       partitioner: partitioning.BasePartitioner,
-      dataset_iterator: Optional[tf.data.Iterator] = None,
+      dataset_iterator: Optional[
+          Union[tf.data.Iterator, clu.data.dataset_iterator.DatasetIterator]
+      ] = None,
       save_dtype: Optional[jnp.dtype] = None,
       restore_dtype: Optional[jnp.dtype] = None,
       keep: Optional[int] = None,
@@ -2276,11 +2292,14 @@ def __init__(
     del keep_dataset_checkpoints
     self._train_state = train_state
     self._partitioner = partitioner
+    if isinstance(
+        dataset_iterator, clu.data.dataset_iterator.TfDatasetIterator
+    ):
+      assert dataset_iterator._checkpoint
     self._dataset_iterator = dataset_iterator
     self._save_dtype = save_dtype
     self._restore_dtype = restore_dtype
     self._tmp_directory: Optional[epath.PathLike] = None
-
     data_layout = partitioner.get_data_layout()
     dataset_ckpt_name = (
         f'{_TRAIN_DS_PREFIX}-'