[continuous batching] singleton pattern for scheduler

src/deepsparse/v2/schedulers/continuous_batching_scheduler.py

@@ -28,11 +28,32 @@
 __all__ = ["ContinuousBatchingScheduler"]
 
 
+_GLOBAL_SCHEDULER = None
+
+
 class ContinuousBatchingScheduler(OperatorScheduler):
     """
     Manages EngineOperator jobs that should be run with continuous batching.
     Groups requests for the same engine into larger batches and returns
-    the result to the respeictive request threads after scheduled completion
+    the result to the respective request threads after scheduled completion
+
+    Example code for getting or creating a shared instance for scheduling
+    between pipelines and adding an engine operator to the scheduler
+    within a pipeline
+
+    ```python
+
+    class MyPipeline(Pipeline):
+
+        def __init__(self):
+            ...
+            engine_operator = EngineOperator(...)
+            ...
+            continuous_batching_scheduler = ContinuousBatchingScheduler.get_instance()
+            continuous_batching_scheduler.add_engine_operator(engine_operator)
+
+            super.__init__(...)
+    ```
 
     :param max_workers: maximum number of threads to execute at once, default 1
     """
@@ -54,6 +75,19 @@ def __init__(self, max_workers: int = 1):
         for worker_thread in self._threads:
             worker_thread.start()
 
+    @classmethod
+    def get_instance(cls) -> "ContinuousBatchingScheduler":
+        """
+        :return: global instance of the continuous batching scheduler. If one
+            does not exist yet, a scheduler with a single worker thread to
+            schedule all jobs is created and started
+        """
+        if _GLOBAL_SCHEDULER is not None:
+            return _GLOBAL_SCHEDULER  # noqa: F823
+
+        _GLOBAL_SCHEDULER = cls(max_workers=1)
+        return _GLOBAL_SCHEDULER
+
     @property
     def max_workers(self) -> int:
         """