Add base class for workflows

docs/source/engines.rst

@@ -15,16 +15,18 @@ Multi-GPU data parallel
 Workflows
 ---------
 
-.. automodule:: monai.engines.workflow
-.. currentmodule:: monai.engines.workflow
+.. currentmodule:: monai.engines
+
+`BaseWorkflow`
+~~~~~~~~~~~~~~
+.. autoclass:: BaseWorkflow
+    :members:
 
 `Workflow`
 ~~~~~~~~~~
 .. autoclass:: Workflow
     :members:
 
-.. currentmodule:: monai.engines
-
 `Trainer`
 ~~~~~~~~~
 .. autoclass:: Trainer

monai/engines/__init__.py

@@ -24,3 +24,4 @@
     engine_apply_transform,
     get_devices_spec,
 )
+from .workflow import BaseWorkflow, Workflow

monai/engines/workflow.py

@@ -10,6 +10,7 @@
 # limitations under the License.
 
 import warnings
+from abc import ABC, abstractmethod
 from typing import TYPE_CHECKING, Callable, Dict, Iterable, List, Optional, Sequence, Union
 
 import torch
@@ -37,6 +38,18 @@
     EventEnum, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EventEnum")
 
 
+class BaseWorkflow(ABC):
+    """
+    Base class for any MONAI style workflow.
+    `run()` is designed to execute the train, evaluation or inference logic.
+
+    """
+
+    @abstractmethod
+    def run(self, *args, **kwargs):
+        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")
+
+
 class Workflow(IgniteEngine):  # type: ignore[valid-type, misc] # due to optional_import
     """
     Workflow defines the core work process inheriting from Ignite engine.