Fix elastic data loading process count divisibility error in MaxText.

src/maxtext/input_pipeline/grain_data_processing.py

@@ -397,18 +397,48 @@ def _get_pipeline_fn(config):
   return pretrain_preprocessing_pipeline
 
 
-def _make_elastic_iterator(dataset, config, preprocessing_fn, shard_index=None, shard_count=None, mp_opts=None):
+def _make_elastic_iterator(
+    dataset,
+    config,
+    preprocessing_fn,
+    shard_index=None,
+    shard_count=None,
+    process_indices=None,
+    mp_opts=None,
+):
   """Applies preprocessing_fn then wraps the result with ElasticIterator.
 
-  When shard_index/shard_count are None, defaults to jax.process_index()/jax.process_count().
+  When shard_index/shard_count are None, defaults to
+  jax.process_index()/jax.process_count() (or calculated from
+  process_indices if provided).
+
+  Args:
+    dataset: The input dataset.
+    config: The hyperparameter configuration.
+    preprocessing_fn: The function to apply before wrapping.
+    shard_index: The shard index. Defaults to None.
+    shard_count: The shard count. Defaults to None.
+    process_indices: The active process indices. Defaults to None.
+    mp_opts: Multiprocessing options. Defaults to None.
   """
   ds = preprocessing_fn(dataset=dataset)
+  if shard_index is None:
+    if process_indices is not None:
+      shard_index = process_indices.index(jax.process_index())
+    else:
+      shard_index = jax.process_index()
+  if shard_count is None:
+    if process_indices is not None:
+      shard_count = len(process_indices)
+    else:
+      shard_count = jax.process_count()
+
   return ElasticIterator(
       ds,
       global_batch_size=config.global_batch_size_to_load,
       shard_options=grain.ShardOptions(
-          shard_index=shard_index if shard_index is not None else jax.process_index(),
-          shard_count=shard_count if shard_count is not None else jax.process_count(),
+          shard_index=shard_index,
+          shard_count=shard_count,
       ),
       read_options=grain.ReadOptions(
           num_threads=config.grain_num_threads,
@@ -463,7 +493,12 @@ def make_grain_train_iterator(
   # pass to MultiHostDataLoadIterator
   if config.colocated_python_data_input:
     if config.grain_use_elastic_iterator:
-      preprocessing_fn = functools.partial(_make_elastic_iterator, config=config, preprocessing_fn=preprocessing_fn)
+      preprocessing_fn = functools.partial(
+          _make_elastic_iterator,
+          config=config,
+          preprocessing_fn=preprocessing_fn,
+          process_indices=process_indices,
+      )
 
     global_shape = (config.global_batch_size_to_load, config.max_target_length)
     return multihost_dataloading.RemoteIteratorWrapper(

src/maxtext/input_pipeline/input_pipeline_interface.py

@@ -100,8 +100,12 @@ def create_data_iterator(config: pyconfig.HyperParameters, mesh):
       mesh,
   )
   output_train_iterator = create_process_specific_iterator(config, mesh, process_indices_train, train_iterator)
+  active_process_count = len(set(d.process_index for d in mesh.devices.flat))
   if config.expansion_factor_real_data > 1:  # assert number of hosts loading real data
-    assert len(process_indices_train) == jax.process_count() // config.expansion_factor_real_data
+    assert (
+        len(process_indices_train)
+        == active_process_count // config.expansion_factor_real_data
+    )
 
   # Generate output eval iterator
   output_eval_iterator = None
@@ -115,6 +119,10 @@ def create_data_iterator(config: pyconfig.HyperParameters, mesh):
     )
 
     if config.expansion_factor_real_data > 1:
-      assert len(process_indices_eval) == jax.process_count() // config.expansion_factor_real_data
+      assert (
+          len(process_indices_eval)
+          == active_process_count // config.expansion_factor_real_data
+      )
+
     output_eval_iterator = create_process_specific_iterator(config, mesh, process_indices_eval, eval_iterator)
   return output_train_iterator, output_eval_iterator