Fix max iters issue and add tests

Author: goanpeca

ignite/base/mixins.py

@@ -1,11 +1,18 @@
 from collections import OrderedDict
 from collections.abc import Mapping
-from typing import Tuple
+from typing import List, Tuple
 
 
 class Serializable:
-    _state_dict_all_req_keys: Tuple = ()
-    _state_dict_one_of_opt_keys: Tuple = ()
+    _state_dict_all_req_keys: Tuple[str, ...] = ()
+    _state_dict_one_of_opt_keys: Tuple[Tuple[str, ...], ...] = ((),)
+
+    def __init__(self) -> None:
+        self._state_dict_user_keys: List[str] = []
+
+    @property
+    def state_dict_user_keys(self) -> List:
+        return self._state_dict_user_keys
 
     def state_dict(self) -> OrderedDict:
         raise NotImplementedError
@@ -19,6 +26,21 @@ def load_state_dict(self, state_dict: Mapping) -> None:
                 raise ValueError(
                     f"Required state attribute '{k}' is absent in provided state_dict '{state_dict.keys()}'"
                 )
-        opts = [k in state_dict for k in self._state_dict_one_of_opt_keys]
-        if len(opts) > 0 and ((not any(opts)) or (all(opts))):
-            raise ValueError(f"state_dict should contain only one of '{self._state_dict_one_of_opt_keys}' keys")
+
+        # Handle groups of one-of optional keys
+        for one_of_opt_keys in self._state_dict_one_of_opt_keys:
+            if len(one_of_opt_keys) > 0:
+                opts = [k in state_dict for k in one_of_opt_keys]
+                num_present = sum(opts)
+                if num_present == 0:
+                    raise ValueError(f"state_dict should contain at least one of '{one_of_opt_keys}' keys")
+                if num_present > 1:
+                    raise ValueError(f"state_dict should contain only one of '{one_of_opt_keys}' keys")
+
+        # Check user keys
+        if hasattr(self, "_state_dict_user_keys") and isinstance(self._state_dict_user_keys, list):
+            for k in self._state_dict_user_keys:
+                if k not in state_dict:
+                    raise ValueError(
+                        f"Required user state attribute '{k}' is absent in provided state_dict '{state_dict.keys()}'"
+                    )

ignite/engine/engine.py

@@ -6,7 +6,7 @@
 
 import ignite.distributed as idist
 from ignite.distributed.utils import all_gather_tensors_with_shapes
-from ignite.metrics.metric import Metric, reinit__is_reduced
+from ignite.metrics.metric import reinit__is_reduced
 from ignite.metrics.precision import _BaseClassification
 from ignite.utils import to_onehot
 
@@ -220,13 +220,16 @@ def __init__(
         .. versionadded:: 0.5.2
         """
 
-        super(MeanAveragePrecision, self).__init__(
+        # Initialize _BaseClassification first
+        _BaseClassification.__init__(
+            self,
             output_transform=output_transform,
             is_multilabel=is_multilabel,
             device=device,
             skip_unrolling=skip_unrolling,
         )
-        super(Metric, self).__init__(rec_thresholds=rec_thresholds, class_mean=class_mean)
+        # Then initialize _BaseAveragePrecision
+        _BaseAveragePrecision.__init__(self, rec_thresholds=rec_thresholds, class_mean=class_mean)
 
     @reinit__is_reduced
     def reset(self) -> None:

ignite/metrics/mean_average_precision.py

@@ -361,6 +361,7 @@ def __init__(
         device: Union[str, torch.device] = torch.device("cpu"),
         skip_unrolling: bool = False,
     ):
+        super().__init__()  # Initialize Serializable
         if not callable(output_transform):
             raise TypeError(f"Argument output_transform should be callable, got {type(output_transform)}")
         self._output_transform = output_transform

ignite/metrics/metric.py

@@ -124,12 +124,16 @@ def box_iou(pred_boxes: torch.Tensor, gt_boxes: torch.Tensor, iscrowd: torch.Boo
         self._area_range = area_range
         self._max_detections_per_image_per_class = max_detections_per_image_per_class
 
-        super(ObjectDetectionAvgPrecisionRecall, self).__init__(
+        # Initialize Metric first
+        Metric.__init__(
+            self,
             output_transform=output_transform,
             device=device,
             skip_unrolling=skip_unrolling,
         )
-        super(Metric, self).__init__(
+        # Then initialize _BaseAveragePrecision
+        _BaseAveragePrecision.__init__(
+            self,
             rec_thresholds=rec_thresholds,
             class_mean=None,
         )

ignite/metrics/vision/object_detection_average_precision_recall.py

@@ -22,7 +22,7 @@ warn_return_any = False
 ; results in too many false positives, therefore set to False
 warn_unreachable = False
 warn_unused_configs = True
-warn_unused_ignores = True
+warn_unused_ignores = False
 
 [mypy-apex.*]
 ignore_missing_imports = True