[DLMED] fix flake8 issue

Signed-off-by: Nic Ma <nma@nvidia.com>

monai/handlers/iteration_metric.py

@@ -17,17 +17,13 @@
 from monai.metrics import do_metric_reduction
 from monai.utils import MetricReduction, exact_version, optional_import
 
-NotComputableError, _ = optional_import("ignite.exceptions", "0.4.2", exact_version, "NotComputableError")
 idist, _ = optional_import("ignite", "0.4.2", exact_version, "distributed")
 Metric, _ = optional_import("ignite.metrics", "0.4.2", exact_version, "Metric")
 reinit__is_reduced, _ = optional_import("ignite.metrics.metric", "0.4.2", exact_version, "reinit__is_reduced")
 if TYPE_CHECKING:
     from ignite.engine import Engine
-    from ignite.metrics import EpochWise, MetricUsage
 else:
     Engine, _ = optional_import("ignite.engine", "0.4.2", exact_version, "Engine")
-    MetricUsage, _ = optional_import("ignite.metrics", "0.4.2", exact_version, "MetricUsage")
-    EpochWise, _ = optional_import("ignite.metrics", "0.4.2", exact_version, "EpochWise")
 
 
 class IterationMetric(Metric):  # type: ignore[valid-type, misc] # due to optional_import
@@ -113,20 +109,19 @@ def compute(self) -> Any:
     def _reduce(self, scores) -> Any:
         return do_metric_reduction(scores, MetricReduction.MEAN)[0]
 
-    def attach(self, engine: Engine, name: str, usage: Union[str, MetricUsage] = EpochWise()) -> None:
+    def attach(self, engine: Engine, name: str) -> None:
         """
         Attaches current metric to provided engine. On the end of engine's run,
         `engine.state.metrics` dictionary will contain computed metric's value under provided name.
 
         Args:
             engine: the engine to which the metric must be attached.
-            name: the name of the metric to attach
-            usage: the usage of the metric.
+            name: the name of the metric to attach.
 
         """
-        super().attach(engine=engine, name=name, usage=usage)
+        super().attach(engine=engine, name=name)
         # FIXME: record engine for communication, ignite will support it in the future version soon
         self.engine = engine
         self.name = name
         if self.save_details and not hasattr(engine.state, "metric_details"):
-            setattr(engine.state, "metric_details", dict())
+            engine.state.metric_details = dict()

monai/handlers/metrics_saver.py

@@ -13,7 +13,6 @@
 from typing import TYPE_CHECKING, Callable, Optional, Sequence, Union
 
 import numpy as np
-import torch
 
 from monai.utils import ensure_tuple, exact_version, optional_import
 from monai.utils.module import get_torch_version_tuple
@@ -101,7 +100,7 @@ def __call__(self, engine: Engine) -> None:
                 with open(os.path.join(self.save_dir, "metrics.csv"), "w") as f:
                     for k, v in engine.state.metrics.items():
                         if k in self.metrics or "*" in self.metrics:
-                            f.write(f"f{k}\t{str(v)}\n")
+                            f.write(f"{k}\t{str(v)}\n")
 
         if (
             self.metric_details is not None
@@ -137,5 +136,7 @@ def __call__(self, engine: Engine) -> None:
                                 f.write("class\tmean\tmedian\tmax\tmin\t90percent\tstd\n")
                                 for i, d in enumerate(v.transpose()):
                                     f.write(
-                                        f"{labels[i]}\t{np.nanmean(d):.4f}\t{np.nanmedian(d):.4f}\t{np.nanmax(d):.4f}\t{np.nanmin(d):.4f}\t{np.nanpercentile(d, 10):.4f}\t{np.nanstd(d):.4f}\n"
+                                        f"{labels[i]}\t{np.nanmean(d):.4f}\t{np.nanmedian(d):.4f}\t"
+                                        f"{np.nanmax(d):.4f}\t{np.nanmin(d):.4f}\t"
+                                        f"{np.nanpercentile(d, 10):.4f}\t{np.nanstd(d):.4f}\n"
                                     )

monai/handlers/utils.py

@@ -12,7 +12,6 @@
 from typing import TYPE_CHECKING, Any, Callable
 
 import torch
-import torch.distributed as dist
 
 from monai.utils import exact_version, optional_import
 

tests/test_handler_mean_dice.py

@@ -12,7 +12,7 @@
 import unittest
 
 import torch
-from ignite.engine import Engine, Events
+from ignite.engine import Engine
 from parameterized import parameterized
 
 from monai.handlers import MeanDice