Fault Tolerant Manual: Add _rotate_worker_indices utility (#10647)

CHANGELOG.md

@@ -15,6 +15,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fault Tolerant Manual
     * Add `_SupportsStateDict` protocol to detect if classes are stateful ([#10646](https://github.com/PyTorchLightning/pytorch-lightning/issues/10646))
     * Add `_FaultTolerantMode` enum used to track different supported fault tolerant modes ([#10645](https://github.com/PyTorchLightning/pytorch-lightning/issues/10645))
+    * Add a `_rotate_worker_indices` utility to reload the state according the latest worker ([#10647](https://github.com/PyTorchLightning/pytorch-lightning/issues/10647))
 
 
 -

pytorch_lightning/utilities/auto_restart.py

@@ -247,14 +247,7 @@ class CaptureMapDataset(Dataset):
     def load_state_dict(self, state_dict: Dict[int, Any], latest_worker_id: int, num_workers: int) -> None:
         # as workers aren't available, the ``state_dict``` is cached until workers are made available.
         state_dict = deepcopy(state_dict)
-
-        if num_workers > 0:
-            # remap states to worker ids starting at 0
-            next_worker_id = latest_worker_id + 1
-            old_to_new_worker_id_map = [((next_worker_id + i) % num_workers, i) for i in range(num_workers)]
-            state_dict = {
-                new_id: state_dict[old_id] for old_id, new_id in old_to_new_worker_id_map if old_id in state_dict
-            }
+        state_dict = _rotate_worker_indices(state_dict, latest_worker_id, num_workers)
         self._cached_state_dict = state_dict
 
     def state_dict(self) -> Dict[int, Dict[str, Any]]:
@@ -573,6 +566,20 @@ def reload_dataloader_state_dict(dataloader: DataLoader, state_dict: Dict[str, A
         raise MisconfigurationException("This shouldn't happen. Please, open an issue on PyTorch Lightning Github.")
 
 
+def _rotate_worker_indices(state: Dict[int, Any], latest_worker_id: int, num_workers: int) -> Dict[int, Any]:
+    """This function is used to rotate the worker indices based on the `latest_worker_id` the training failed
+    on."""
+    if num_workers == 0:
+        return state
+    if latest_worker_id > num_workers - 1:
+        raise MisconfigurationException("The `latest_worker_id` should be within [0, num_workers - 1].")
+    if len(state) != num_workers:
+        raise MisconfigurationException("The `state` should contain `num_workers - 1` values.")
+    next_worker_id = latest_worker_id + 1
+    old_to_new_worker_id_map = [((next_worker_id + i) % num_workers, i) for i in range(num_workers)]
+    return {new_id: state[old_id] for old_id, new_id in old_to_new_worker_id_map if old_id in state}
+
+
 @runtime_checkable
 class _SupportsStateDict(Protocol):
     """This class is used to detect if an object is stateful using `isinstance(obj, _SupportsStateDict)`."""

tests/utilities/test_auto_restart.py

@@ -40,6 +40,7 @@ from pytorch_lightning.utilities.auto_restart import (
     _add_capture_metadata_collate,
     _dataloader_load_state_dict,
     _dataloader_to_state_dict,
+    _rotate_worker_indices,
     _SupportsStateDict,
     CaptureIterableDataset,
     CaptureMapDataset,
@@ -1196,6 +1197,19 @@ def test_auto_restart_under_signal(on_last_batch, val_check_interval, failure_on
         assert "dataloader_state_dict" in state_dict
 
 
+def test_rotate_worker_indices():
+    """This test ensures `worker_id` are rotated properly depending on which one was the latest."""
+    state_dict = {0: 0, 1: 1}
+    assert _rotate_worker_indices(state_dict, 0, 2) == {0: 1, 1: 0}
+    assert _rotate_worker_indices(state_dict, 1, 2) == {0: 0, 1: 1}
+
+    with pytest.raises(MisconfigurationException, match="The `latest_worker_id` should be within"):
+        _rotate_worker_indices(state_dict, 2, 2)
+
+    with pytest.raises(MisconfigurationException, match="The `state` should contain"):
+        _rotate_worker_indices(state_dict, 2, 3)
+
+
 def test_supports_state_dict_protocol():
     class StatefulClass:
         def state_dict(self):