change from **kwargs: Mapping to **kwargs: Any

Author: RaviTezu

ignite/contrib/engines/common.py

@@ -47,7 +47,7 @@ def setup_common_training_handlers(
     stop_on_nan: Optional[bool] = True,
     clear_cuda_cache: Optional[bool] = True,
     save_handler: Optional[Union[Callable, BaseSaveHandler]] = None,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Helper method to setup trainer with common handlers (it also supports distributed configuration):
         - :class:`~ignite.handlers.TerminateOnNan`
@@ -137,7 +137,7 @@ def _setup_common_training_handlers(
     stop_on_nan: Optional[bool] = True,
     clear_cuda_cache: Optional[bool] = True,
     save_handler: Optional[Union[Callable, BaseSaveHandler]] = None,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     if output_path is not None and save_handler is not None:
         raise ValueError(
@@ -219,7 +219,7 @@ def _setup_common_distrib_training_handlers(
     stop_on_nan: Optional[bool] = True,
     clear_cuda_cache: Optional[bool] = True,
     save_handler: Optional[Union[Callable, BaseSaveHandler]] = None,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
 
     _setup_common_training_handlers(
@@ -313,7 +313,7 @@ def setup_tb_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup TensorBoard logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -344,7 +344,7 @@ def setup_visdom_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup Visdom logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -374,7 +374,7 @@ def setup_mlflow_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup MLflow logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -404,7 +404,7 @@ def setup_neptune_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup Neptune logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -434,7 +434,7 @@ def setup_wandb_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup WandB logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -464,7 +464,7 @@ def setup_plx_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup Polyaxon logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -494,7 +494,7 @@ def setup_trains_logging(
     optimizers: Optional[Union[Optimizer, Dict[str, Optimizer]]] = None,
     evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
     log_every_iters: Optional[int] = 100,
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method to setup Trains logging on trainer and a list of evaluators. Logged metrics are:
         - Training metrics, e.g. running average loss values
@@ -535,7 +535,7 @@ def gen_save_best_models_by_val_score(
     n_saved: Optional[int] = 3,
     trainer: Optional[Engine] = None,
     tag: Optional[str] = "val",
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method adds a handler to ``evaluator`` to save ``n_saved`` of best models based on the metric
     (named by ``metric_name``) provided by ``evaluator`` (i.e. ``evaluator.state.metrics[metric_name]``).
@@ -593,7 +593,7 @@ def save_best_model_by_val_score(
     n_saved: Optional[int] = 3,
     trainer: Optional[Engine] = None,
     tag: Optional[str] = "val",
-    **kwargs: Mapping,
+    **kwargs: Any,
 ):
     """Method adds a handler to ``evaluator`` to save on a disk ``n_saved`` of best models based on the metric
     (named by ``metric_name``) provided by ``evaluator`` (i.e. ``evaluator.state.metrics[metric_name]``).

ignite/contrib/handlers/base_logger.py

@@ -166,7 +166,7 @@ def attach(self, engine: Engine, log_handler: Callable, event_name: Any):
 
         return engine.add_event_handler(event_name, log_handler, self, name)
 
-    def attach_output_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Mapping):
+    def attach_output_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Any):
         """Shortcut method to attach `OutputHandler` to the logger.
 
         Args:
@@ -182,7 +182,7 @@ def attach_output_handler(self, engine: Engine, event_name: Any, *args: Any, **k
         """
         return self.attach(engine, self._create_output_handler(*args, **kwargs), event_name=event_name)
 
-    def attach_opt_params_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Mapping):
+    def attach_opt_params_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Any):
         """Shortcut method to attach `OptimizerParamsHandler` to the logger.
 
         Args:
@@ -199,11 +199,11 @@ def attach_opt_params_handler(self, engine: Engine, event_name: Any, *args: Any,
         self.attach(engine, self._create_opt_params_handler(*args, **kwargs), event_name=event_name)
 
     @abstractmethod
-    def _create_output_handler(self, engine, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, engine, *args: Any, **kwargs: Any):
         pass
 
     @abstractmethod
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         pass
 
     def __enter__(self):

ignite/contrib/handlers/mlflow_logger.py

@@ -113,10 +113,10 @@ def close(self):
 
         mlflow.end_run()
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 

ignite/contrib/handlers/neptune_logger.py

@@ -182,7 +182,7 @@ def __getattr__(self, attr: Any):
 
         return getattr(neptune, attr)
 
-    def __init__(self, *args: Any, **kwargs: Mapping):
+    def __init__(self, *args: Any, **kwargs: Any):
         try:
             import neptune
         except ImportError:
@@ -208,10 +208,10 @@ def __init__(self, *args: Any, **kwargs: Mapping):
     def close(self):
         self.stop()
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 

ignite/contrib/handlers/param_scheduler.py

@@ -583,7 +583,7 @@ def simulate_values(
         schedulers: List[ParamScheduler],
         durations: List[int],
         param_names: Union[List[str], Tuple[str]] = None,
-        **kwargs: Mapping,
+        **kwargs: Any,
     ):
         """Method to simulate scheduled values during num_events events.
 
@@ -706,7 +706,7 @@ def get_param(self) -> Union[float, List[float]]:
             return lr_list
 
     @classmethod
-    def simulate_values(cls, num_events: int, lr_scheduler: _LRScheduler, **kwargs: Mapping):
+    def simulate_values(cls, num_events: int, lr_scheduler: _LRScheduler, **kwargs: Any):
         """Method to simulate scheduled values during num_events events.
 
         Args:
@@ -1081,7 +1081,7 @@ def load_state_dict(self, state_dict: Dict):
             s.load_state_dict(sd)
 
     @classmethod
-    def simulate_values(cls, num_events: int, schedulers: _LRScheduler, **kwargs: Mapping):
+    def simulate_values(cls, num_events: int, schedulers: _LRScheduler, **kwargs: Any):
         """Method to simulate scheduled values during num_events events.
 
         Args:
@@ -1119,7 +1119,7 @@ def simulate_values(cls, num_events: int, schedulers: _LRScheduler, **kwargs: Ma
             return values
 
 
-def _get_fake_optimizer(optimizer_cls: Optional[Optimizer] = None, **kwargs: Mapping):
+def _get_fake_optimizer(optimizer_cls: Optional[Optimizer] = None, **kwargs: Any):
     t = torch.zeros([1], requires_grad=True)
     if optimizer_cls is None:
         optimizer_cls = torch.optim.SGD

ignite/contrib/handlers/polyaxon_logger.py

@@ -91,7 +91,7 @@ class PolyaxonLogger(BaseLogger):
 
     """
 
-    def __init__(self, *args: Any, **kwargs: Mapping):
+    def __init__(self, *args: Any, **kwargs: Any):
         try:
             from polyaxon_client.tracking import Experiment
         except ImportError:
@@ -105,10 +105,10 @@ def __init__(self, *args: Any, **kwargs: Mapping):
     def __getattr__(self, attr: Any):
         return getattr(self.experiment, attr)
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 

ignite/contrib/handlers/tensorboard_logger.py

@@ -149,7 +149,7 @@ class TensorboardLogger(BaseLogger):
 
     """
 
-    def __init__(self, *args: Any, **kwargs: Mapping):
+    def __init__(self, *args: Any, **kwargs: Any):
         try:
             from tensorboardX import SummaryWriter
         except ImportError:
@@ -167,10 +167,10 @@ def __init__(self, *args: Any, **kwargs: Mapping):
     def close(self):
         self.writer.close()
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 

ignite/contrib/handlers/tqdm_logger.py

@@ -200,14 +200,14 @@ def attach(
         super(ProgressBar, self).attach(engine, log_handler, event_name)
         engine.add_event_handler(closing_event_name, self._close)
 
-    def attach_opt_params_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Mapping):
+    def attach_opt_params_handler(self, engine: Engine, event_name: Any, *args: Any, **kwargs: Any):
         """Intentionally empty"""
         pass
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return _OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         """Intentionally empty"""
         pass
 

ignite/contrib/handlers/trains_logger.py

@@ -119,7 +119,7 @@ class TrainsLogger(BaseLogger):
 
     """
 
-    def __init__(self, *_, **kwargs: Mapping):
+    def __init__(self, *_, **kwargs: Any):
         try:
             from trains import Task
             from trains.binding.frameworks.tensorflow_bind import WeightsGradientHistHelper
@@ -184,10 +184,10 @@ def bypass_mode(cls) -> bool:
     def close(self):
         self.trains_logger.flush()
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 
@@ -632,7 +632,7 @@ class TrainsSaver(DiskSaver):
     """
 
     def __init__(
-        self, logger: TrainsLogger = None, output_uri: str = None, dirname: str = None, *args: Any, **kwargs: Mapping
+        self, logger: TrainsLogger = None, output_uri: str = None, dirname: str = None, *args: Any, **kwargs: Any
     ):
 
         self._setup_check_trains(logger, output_uri)

ignite/contrib/handlers/visdom_logger.py

@@ -138,7 +138,7 @@ class VisdomLogger(BaseLogger):
 
     """
 
-    def __init__(self, server=None, port=None, num_workers=1, raise_exceptions=True, **kwargs: Mapping):
+    def __init__(self, server=None, port=None, num_workers=1, raise_exceptions=True, **kwargs: Any):
         try:
             import visdom
         except ImportError:
@@ -195,10 +195,10 @@ def close(self):
         self.executor.shutdown()
         self.vis = None
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)
 
 
@@ -553,11 +553,11 @@ def __init__(self, result: Any):
         def result(self):
             return self._output
 
-    def __init__(self, *args: Any, **kwargs: Mapping):
+    def __init__(self, *args: Any, **kwargs: Any):
         pass
 
-    def submit(self, fn: Callable, **kwargs: Mapping):
+    def submit(self, fn: Callable, **kwargs: Any):
         return _DummyExecutor._DummyFuture(fn(**kwargs))
 
-    def shutdown(self, *args: Any, **kwargs: Mapping):
+    def shutdown(self, *args: Any, **kwargs: Any):
         pass

ignite/contrib/handlers/wandb_logger.py

@@ -116,7 +116,7 @@ def score_function(engine):
             evaluator.add_event_handler(Events.COMPLETED, model_checkpoint, {'model': model})
     """
 
-    def __init__(self, *args: Any, **kwargs: Mapping):
+    def __init__(self, *args: Any, **kwargs: Any):
         try:
             import wandb
 
@@ -132,10 +132,10 @@ def __init__(self, *args: Any, **kwargs: Mapping):
     def __getattr__(self, attr: Any):
         return getattr(self._wandb, attr)
 
-    def _create_output_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_output_handler(self, *args: Any, **kwargs: Any):
         return OutputHandler(*args, **kwargs)
 
-    def _create_opt_params_handler(self, *args: Any, **kwargs: Mapping):
+    def _create_opt_params_handler(self, *args: Any, **kwargs: Any):
         return OptimizerParamsHandler(*args, **kwargs)