Few other fixes

Author: vfdev-5

ignite/handlers/checkpoint.py

@@ -6,7 +6,7 @@
 from abc import ABCMeta, abstractmethod
 from collections import OrderedDict
 from pathlib import Path
-from typing import Any, Callable, cast, Dict, List, Mapping, NamedTuple, Optional, Tuple, Union
+from typing import Any, Callable, cast, Dict, List, Mapping, NamedTuple, Optional, Union
 
 import torch
 import torch.nn as nn
@@ -277,7 +277,7 @@ class Checkpoint(Serializable):
     """
 
     Item = NamedTuple("Item", [("priority", int), ("filename", str)])
-    _state_dict_all_req_keys = ("saved",)
+    _state_dict_all_req_keys = ("_saved",)
 
     def __init__(
         self,
@@ -707,11 +707,12 @@ def reload_objects(self, to_load: Mapping, load_kwargs: Optional[Dict] = None, *
 
         Checkpoint.load_objects(to_load=to_load, checkpoint=path, **load_kwargs)
 
-    def state_dict(self) -> OrderedDict[str, List[Tuple[int, str]]]:
+    def state_dict(self) -> OrderedDict:
         """Method returns state dict with saved items: list of ``(priority, filename)`` pairs.
         Can be used to save internal state of the class.
         """
-        return OrderedDict([("saved", [(p, f) for p, f in self._saved])])
+        # TODO: this method should use _state_dict_all_req_keys
+        return OrderedDict([("_saved", [(p, f) for p, f in self._saved])])
 
     def load_state_dict(self, state_dict: Mapping) -> None:
         """Method replaces internal state of the class with provided state dict data.
@@ -720,7 +721,7 @@ def load_state_dict(self, state_dict: Mapping) -> None:
             state_dict: a dict with "saved" key and list of ``(priority, filename)`` pairs as values.
         """
         super().load_state_dict(state_dict)
-        self._saved = [Checkpoint.Item(p, f) for p, f in state_dict["saved"]]
+        self._saved = [Checkpoint.Item(p, f) for p, f in state_dict["_saved"]]
 
     @staticmethod
     def get_default_score_fn(metric_name: str, score_sign: float = 1.0) -> Callable:

ignite/metrics/metrics_lambda.py

@@ -1,6 +1,4 @@
 import itertools
-from collections import OrderedDict
-from collections.abc import Mapping
 from typing import Any, Callable, Optional, Union
 
 import torch

ignite/utils.py

@@ -111,9 +111,7 @@ def value(self) -> Any:
         return self.collection[self.key]  # type: ignore[index]
 
     @staticmethod
-    def wrap(
-        object: Union[Dict, List], key: Union[int, str], value: Any
-    ) -> Union[Any, "_CollectionItem"]:
+    def wrap(object: Union[Dict, List], key: Union[int, str], value: Any) -> Union[Any, "_CollectionItem"]:
         return (
             _CollectionItem(object, key)
             if value is None or isinstance(value, _CollectionItem.types_as_collection_item)

tests/ignite/handlers/test_checkpoint.py

@@ -1643,7 +1643,7 @@ def test_checkpoint_load_state_dict():
     to_save = {"model": model}
     checkpointer = Checkpoint(to_save, save_handler=save_handler, n_saved=None)
 
-    sd = {"saved": [(0, "model_0.pt"), (10, "model_10.pt"), (20, "model_20.pt")]}
+    sd = {"_saved": [(0, "model_0.pt"), (10, "model_10.pt"), (20, "model_20.pt")]}
     checkpointer.load_state_dict(sd)
     assert checkpointer._saved == true_checkpointer._saved
 

tests/ignite/metrics/test_metric.py

@@ -710,7 +710,7 @@ def _test_creating_on_xla_fails(device):
 @pytest.mark.distributed
 @pytest.mark.skipif(not idist.has_native_dist_support, reason="Skip if no native dist support")
 @pytest.mark.skipif(torch.cuda.device_count() < 1, reason="Skip if no GPU")
-def test_distrib_nccl_gpu(distributed):
+def test_distrib_nccl_gpu(distributed_context_single_node_nccl):
     device = idist.device()
     _test_distrib_sync_all_reduce_decorator(device)
     _test_invalid_sync_all_reduce(device)