Fix for issues related to mypy

ignite/contrib/handlers/neptune_logger.py

@@ -585,7 +585,7 @@ def __call__(self, checkpoint: Mapping, filename: str, metadata: Optional[Mappin
         with tempfile.NamedTemporaryFile() as tmp:
             # we can not use tmp.name to open tmp.file twice on Win32
             # https://docs.python.org/3/library/tempfile.html#tempfile.NamedTemporaryFile
-            torch.save(checkpoint, tmp.file)  # type: ignore[attr-defined]
+            torch.save(checkpoint, tmp.file)
             self._logger.log_artifact(tmp.name, filename)
 
     @idist.one_rank_only(with_barrier=True)

ignite/engine/deterministic.py

@@ -251,12 +251,12 @@ def _from_iteration(self, iteration: int) -> Iterator:
         if isinstance(data, DataLoader):
             try:
                 # following is unsafe for IterableDatasets
-                iteration %= len(data.batch_sampler)  # type: ignore[attr-defined, arg-type]
+                iteration %= len(data.batch_sampler)  # type: ignore[arg-type]
                 # Synchronize dataflow according to state.iteration
                 self._setup_seed()
                 if iteration > 0:
                     # batch sampler is ReproducibleBatchSampler
-                    data.batch_sampler.start_iteration = iteration  # type: ignore[attr-defined, union-attr]
+                    data.batch_sampler.start_iteration = iteration  # type: ignore[union-attr]
                 return iter(data)
             except TypeError as e:
                 # Probably we can do nothing with DataLoader built upon IterableDatasets

ignite/handlers/checkpoint.py

@@ -718,7 +718,7 @@ def _save_func(self, checkpoint: Mapping, path: str, func: Callable, rank: int =
             tmp: Optional[IO[bytes]] = None
             if rank == 0:
                 tmp = tempfile.NamedTemporaryFile(delete=False, dir=self.dirname)
-                tmp_file = tmp.file  # type: ignore
+                tmp_file = tmp.file
                 tmp_name = tmp.name
             try:
                 func(checkpoint, tmp_file, **self.kwargs)

ignite/handlers/param_scheduler.py

@@ -893,7 +893,7 @@ def simulate_values(  # type: ignore[override]
             torch.save(obj, cache_filepath.as_posix())
 
             values = []
-            scheduler = cls(save_history=False, lr_scheduler=lr_scheduler, **kwargs)  # type: ignore[call-arg]
+            scheduler = cls(save_history=False, lr_scheduler=lr_scheduler, **kwargs)
             for i in range(num_events):
                 params = [p[scheduler.param_name] for p in scheduler.optimizer_param_groups]
                 values.append([i] + params)

ignite/handlers/time_profilers.py

@@ -585,7 +585,7 @@ def attach(self, engine: Engine) -> None:
         if not engine.has_event_handler(self._as_first_started):
             engine._event_handlers[Events.STARTED].insert(0, (self._as_first_started, (engine,), {}))
 
-    def get_results(self) -> List[List[Union[str, float]]]:
+    def get_results(self) -> List[List[Union[str, float, Tuple[Union[str, float], Union[str, float]]]]]:
         """
         Method to fetch the aggregated profiler results after the engine is run
 

tests/run_code_style.sh

@@ -12,5 +12,5 @@ elif [ $1 = "fmt" ]; then
 elif [ $1 = "mypy" ]; then
     mypy --config-file mypy.ini
 elif [ $1 = "install" ]; then
-    pip install flake8 "black==21.12b0" "isort==5.7.0" "mypy==0.910"
+    pip install flake8 "black==21.12b0" "isort==5.7.0" "mypy"
 fi