[wip] simplified runner proposal

catalyst/callbacks/checkpoint.py

@@ -25,7 +25,7 @@ def _pack_runner(runner: "IRunner"):
         scheduler=runner.scheduler,
         epoch_metrics=dict(runner.epoch_metrics),
         valid_metrics=dict(runner.valid_metrics),
-        stage_name=runner.stage_name,
+        stage_name=runner.stage,
         epoch=runner.epoch,
         loader_name=runner.loader_name,
         loader_step=runner.loader_batch_step,
@@ -65,8 +65,8 @@ def _load_checkpoint(
     print(f"=> Loading checkpoint {filename}")
     checkpoint = load_checkpoint(filename)
 
-    if not runner.stage_name.startswith("infer") and load_full:
-        runner.stage_name = checkpoint["stage_name"]
+    if not runner.stage.startswith("infer") and load_full:
+        runner.stage = checkpoint["stage_name"]
         runner.epoch = checkpoint["epoch"]
         runner.global_epoch = checkpoint["global_epoch"]
         # @TODO: should we also load,
@@ -620,10 +620,7 @@ def on_epoch_end(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        if (
-            runner.stage_name.startswith("infer")
-            or runner.is_distributed_worker
-        ):
+        if runner.stage.startswith("infer") or runner.is_distributed_worker:
             return
 
         if self.save_n_best > 0:
@@ -644,10 +641,7 @@ def on_stage_end(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        if (
-            runner.stage_name.startswith("infer")
-            or runner.is_distributed_worker
-        ):
+        if runner.stage.startswith("infer") or runner.is_distributed_worker:
             return
         log_message = "Top best models:\n"
         # store latest state

catalyst/callbacks/control_flow.py

@@ -378,7 +378,7 @@ def on_loader_start(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        stage = runner.stage_name
+        stage = runner.stage
         loader = runner.loader_name
         epoch = runner.global_epoch if self.use_global_epochs else runner.epoch
 

catalyst/callbacks/criterion.py

@@ -1,6 +1,7 @@
 from typing import Dict, List, TYPE_CHECKING, Union
 
 from catalyst.callbacks.metric import IBatchMetricCallback
+from catalyst.utils.misc import get_attr
 
 if TYPE_CHECKING:
     from catalyst.core.runner import IRunner
@@ -55,8 +56,8 @@ def on_stage_start(self, runner: "IRunner"):
         Args:
             runner: current runner
         """
-        criterion = runner.get_attr(
-            key="criterion", inner_key=self.criterion_key
+        criterion = get_attr(
+            runner, key="criterion", inner_key=self.criterion_key
         )
         assert criterion is not None
         self._criterion = criterion

catalyst/callbacks/early_stop.py

@@ -120,7 +120,7 @@ def on_epoch_end(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        if runner.stage_name.startswith("infer"):
+        if runner.stage.startswith("infer"):
             return
 
         score = runner.valid_metrics[self.metric]

catalyst/callbacks/optimizer.py

@@ -7,7 +7,7 @@
 from catalyst import registry
 from catalyst.core.callback import Callback, CallbackNode, CallbackOrder
 from catalyst.typing import Optimizer
-from catalyst.utils.misc import maybe_recursive_call
+from catalyst.utils.misc import get_attr, maybe_recursive_call
 from catalyst.utils.torch import get_optimizer_momentum
 
 if TYPE_CHECKING:
@@ -149,8 +149,8 @@ def on_stage_start(self, runner: "IRunner") -> None:
         Args:
             runner(IRunner): current runner
         """
-        self._optimizer = runner.get_attr(
-            key="optimizer", inner_key=self.optimizer_key
+        self._optimizer = get_attr(
+            runner, key="optimizer", inner_key=self.optimizer_key
         )
         # device based optimization step
         if runner.device.type == "xla":
@@ -326,8 +326,8 @@ def on_stage_start(self, runner: "IRunner") -> None:
         """
         from torch.cuda.amp import GradScaler
 
-        self._optimizer = runner.get_attr(
-            key="optimizer", inner_key=self.optimizer_key
+        self._optimizer = get_attr(
+            runner, key="optimizer", inner_key=self.optimizer_key
         )
         self.scaler = GradScaler()
         assert self._optimizer is not None

catalyst/callbacks/scheduler.py

@@ -5,6 +5,7 @@
 
 from catalyst.contrib.nn.schedulers import BatchScheduler, OneCycleLRWithWarmup
 from catalyst.core.callback import Callback, CallbackNode, CallbackOrder
+from catalyst.utils.misc import get_attr
 from catalyst.utils.torch import get_optimizer_momentum
 
 if TYPE_CHECKING:
@@ -173,8 +174,8 @@ def on_stage_start(self, runner: "IRunner") -> None:
         """
         self.reduced_metric = self.reduced_metric or runner.main_metric
 
-        scheduler = runner.get_attr(
-            key="scheduler", inner_key=self.scheduler_key
+        scheduler = get_attr(
+            runner, key="scheduler", inner_key=self.scheduler_key
         )
         assert scheduler is not None
         self._scheduler = scheduler
@@ -297,8 +298,8 @@ def on_stage_start(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        optimizer = runner.get_attr(
-            key="optimizer", inner_key=self.optimizer_key
+        optimizer = get_attr(
+            runner, key="optimizer", inner_key=self.optimizer_key
         )
         assert optimizer is not None
         self._optimizer = optimizer

catalyst/callbacks/validation.py

@@ -33,7 +33,7 @@ def on_epoch_end(self, runner: "IRunner") -> None:
         Args:
             runner: current runner
         """
-        if runner.stage_name.startswith("infer"):
+        if runner.stage.startswith("infer"):
             return
 
         runner.valid_metrics = {

catalyst/contrib/callbacks/telegram_logger.py

@@ -76,7 +76,7 @@ def _send_text(self, text: str):
     def on_stage_start(self, runner: "IRunner"):
         """Notify about starting a new stage."""
         if self.log_on_stage_start:
-            text = f"{runner.stage_name} stage was started"
+            text = f"{runner.stage} stage was started"
 
             self._send_text(text)
 
@@ -115,7 +115,7 @@ def on_loader_end(self, runner: "IRunner"):
     def on_stage_end(self, runner: "IRunner"):
         """Notify about finishing a stage."""
         if self.log_on_stage_end:
-            text = f"{runner.stage_name} stage was finished"
+            text = f"{runner.stage} stage was finished"
 
             self._send_text(text)
 

catalyst/core/callback.py

@@ -5,6 +5,96 @@
     from catalyst.core.runner import IRunner
 
 
+class ICallback:
+    def on_experiment_start(self, runner: "IRunner"):
+        """Event handler for stage start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_stage_start(self, runner: "IRunner"):
+        """Event handler for stage start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_epoch_start(self, runner: "IRunner"):
+        """Event handler for epoch start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_loader_start(self, runner: "IRunner"):
+        """Event handler for loader start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_batch_start(self, runner: "IRunner"):
+        """Event handler for batch start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_batch_end(self, runner: "IRunner"):
+        """Event handler for batch end.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_loader_end(self, runner: "IRunner"):
+        """Event handler for loader end.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_epoch_end(self, runner: "IRunner"):
+        """Event handler for epoch end.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_stage_end(self, runner: "IRunner"):
+        """Event handler for stage end.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_experiment_end(self, runner: "IRunner"):
+        """Event handler for stage start.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+    def on_exception(self, runner: "IRunner"):
+        """Event handler for exception case.
+
+        Args:
+            runner: IRunner instance.
+        """
+        pass
+
+
 class CallbackNode(IntFlag):
     """Callback node usage flag during distributed training.
 
@@ -78,7 +168,7 @@ class CallbackScope(IntFlag):
     Experiment = experiment = 1  # noqa: WPS115
 
 
-class Callback:
+class Callback(ICallback):
     """
     An abstraction that lets you customize your experiment run logic.
     To give users maximum flexibility and extensibility Catalyst supports
@@ -136,78 +226,6 @@ def __init__(
         self.order = order
         self.scope = scope
 
-    def on_stage_start(self, runner: "IRunner"):
-        """Event handler for stage start.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_stage_end(self, runner: "IRunner"):
-        """Event handler for stage end.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_epoch_start(self, runner: "IRunner"):
-        """Event handler for epoch start.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_epoch_end(self, runner: "IRunner"):
-        """Event handler for epoch end.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_loader_start(self, runner: "IRunner"):
-        """Event handler for loader start.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_loader_end(self, runner: "IRunner"):
-        """Event handler for loader end.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_batch_start(self, runner: "IRunner"):
-        """Event handler for batch start.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_batch_end(self, runner: "IRunner"):
-        """Event handler for batch end.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
-    def on_exception(self, runner: "IRunner"):
-        """Event handler for exception case.
-
-        Args:
-            runner: IRunner instance.
-        """
-        pass
-
 
 class CallbackWrapper(Callback):
     """Enable/disable callback execution."""