Use inheritance to re-use code.

Author: koparasy

src/AMSWorkflow/ams_wf/ams_deploy.py

@@ -74,7 +74,17 @@ def name(self):
         return self._name
 
 
-class SequentialExecutor:
+class AMSJobScheduler:
+    def __init__(self, stager_job_generator, config):
+        self._flux_handle = flux.Flux()
+        logger.debug("Preparing user app job specification")
+        self._user_app = JobSpec("user_app", config["user_app"], exclusive=True)
+        self._ml_train = JobSpec("ml_training", config["ml_training"], exclusive=True)
+        self._ml_pruner = JobSpec("ml_pruner", config["ml_pruner"], exclusive=True)
+        self._stager = JobSpec("ams_stager", stager_job_generator(config), exclusive=True)
+
+
+class AMSSequentialJobScheduler(AMSJobScheduler):
     def __init__(self, config):
         def create_fs_stager_job_descr(user_descr):
             config = dict()
@@ -97,7 +107,7 @@ def create_fs_stager_job_descr(user_descr):
                 "--class",
                 user_descr["stager"]["pruner_class"],
                 "--load",
-                "./build_borax/examples/prune.py",
+                user_descr["stager"]["pruner_path"],
             ] + user_descr["stager"]["pruner_args"]
 
             config["resources"] = {
@@ -110,17 +120,7 @@ def create_fs_stager_job_descr(user_descr):
 
             return config
 
-        self._flux_handle = flux.Flux()
-        logger.debug("Preparing user app job specification")
-        self._user_app = JobSpec("user_app", config["user_app"], exclusive=True)
-        self._ml_train = JobSpec("ml_training", config["ml_training"], exclusive=True)
-        self._ml_pruner = JobSpec("ml_pruner", config["ml_pruner"], exclusive=True)
-        self._stager = JobSpec("ams_stager", create_fs_stager_job_descr(config), exclusive=True)
-
-    #        logger.debug("Preparing ml sub selection specification")
-    #        self._ml_subselect = JobSpec("ml_subselect", config["ml_subselect"])
-    # Build the pruning module
-    # TODO Add pruner stage here
+        super().__init__(config, create_fs_stager_job_descr)
 
     def execute(self):
         def execute_and_wait(job_descr, handle):
@@ -134,16 +134,10 @@ def execute_and_wait(job_descr, handle):
                 return False
             return True
 
-        if not execute_and_wait(self._user_app, self._flux_handle):
-            return False
-
-        if not execute_and_wait(self._stager, self._flux_handle):
-            return False
-        if not execute_and_wait(self._ml_pruner, self._flux_handle):
-            return False
+        for step in [self._user_app, self._stager, self._ml_pruner, self._ml_train]:
+            if not execute_and_wait(step, self._flux_handle):
+                return False
 
-        if not execute_and_wait(self._ml_train, self._flux_handle):
-            return False
         return True
 
 
@@ -161,7 +155,7 @@ def deploy(config):
         # TODO Launch concurrent execution
         pass
     elif config["execution_mode"] == "sequential":
-        executor = SequentialExecutor(config)
+        executor = AMSSequentialJobScheduler(config)
         return executor.execute()