draft: some more unit test updates (working up to process_pipeline_request)

Author: vanessavmac

ami/jobs/tests.py

@@ -2,8 +2,10 @@
 import logging
 import time
 
+from django.db import connection
+
 # import pytest
-from django.test import TestCase
+from django.test import TestCase, TransactionTestCase
 from guardian.shortcuts import assign_perm
 from rest_framework.test import APIRequestFactory, APITestCase
 
@@ -210,7 +212,7 @@ def test_cancel_job(self):
         pass
 
 
-class TestMLJobBatchProcessing(TestCase):
+class TestMLJobBatchProcessing(TransactionTestCase):
     def setUp(self):
         self.project = Project.objects.first()  # get the original test project
         assert self.project
@@ -382,9 +384,11 @@ def get_ml_subtask_details(task_name, job):
             return details
 
         job.run()
+        connection.commit()
+        job.refresh_from_db()
 
         start_time = time.time()
-        timeout = 10  # seconds
+        timeout = 30  # seconds
         elapsed_time = 0
 
         while elapsed_time < timeout:

ami/ml/models/pipeline.py

@@ -164,7 +164,9 @@ def collect_images(
 def process_pipeline_request(pipeline_request: dict, project_id: int):
     # TODO: instead of dict can we use pipeline request object?
     """
-    Placeholder for the processing service's request processing logic
+    This is the primary function for processing images on the antenna side.
+    Workers have a function of the same name which will run their own inference/processing logic.
+    On the antenna side, we use external servers via an API to process images.
     """
     request_data = PipelineRequest(**pipeline_request)
     source_image_requests = request_data.source_images

ami/ml/tasks.py

@@ -137,6 +137,4 @@ def check_ml_job_status(ml_job_id: int):
         from django.db import transaction
 
         logger.info(f"ML Job {ml_job_id} still in progress. Checking again for completed tasks.")
-        transaction.on_commit(
-            lambda: check_ml_job_status.apply_async([ml_job_id], countdown=10)
-        )  # check again in 10 seconds
+        transaction.on_commit(lambda: check_ml_job_status.apply_async([ml_job_id]))  # check again in 10 seconds