feature: extend list_jobs_by_share for quota_share_name

sagemaker-train/src/sagemaker/train/aws_batch/batch_api_helper.py

@@ -46,7 +46,7 @@ def _submit_service_job(
         timeout: Set with value of timeout if specified, else default to 1 day.
         share_identifier: value of shareIdentifier if specified.
         tags: A dict of string to string representing Batch tags.
-        quota_share_name: Quota Share name for the Batch job.
+        quota_share_name: value of quotaShareName if specified.
         preemption_config: Preemption configuration.
 
     Returns:

sagemaker-train/src/sagemaker/train/aws_batch/training_queue.py

@@ -71,6 +71,11 @@ def submit(
             raise ValueError(
                 "TrainingQueue requires using a ModelTrainer with Mode.SAGEMAKER_TRAINING_JOB"
             )
+
+        if share_identifier != None and quota_share_name != None:
+            raise ValueError(
+                "Either share_identifier or quota_share_name can be specified, but not both"
+            )
         training_payload = training_job._create_training_job_args(
             input_data_config=inputs, boto3=True
         )
@@ -108,6 +113,7 @@ def map(
         share_identifier: Optional[str] = None,
         timeout: Optional[Dict] = None,
         tags: Optional[Dict] = None,
+        quota_share_name: Optional[str] = None,
     ) -> List[TrainingQueuedJob]:
         """Submit queued jobs to the provided estimator and return a list of TrainingQueuedJob objects.
 
@@ -120,6 +126,7 @@ def map(
             share_identifier: Share identifier for the Batch jobs.
             timeout: Timeout configuration for the Batch jobs.
             tags: Tags apply to Batch job. These tags are for Batch job only.
+            quota_share_name: Quota share name for the Batch jobs.
 
         Returns: a list of TrainingQueuedJob objects with each Batch job ARN and job name.
 
@@ -144,6 +151,7 @@ def map(
                 share_identifier,
                 timeout,
                 tags,
+                quota_share_name,
             )
             queued_batch_job_list.append(queued_batch_job)
 
@@ -171,7 +179,7 @@ def list_jobs(
             for job_result in job_result_dict.get("jobSummaryList", []):
                 if "jobArn" in job_result and "jobName" in job_result:
                     jobs_to_return.append(
-                        TrainingQueuedJob(job_result["jobArn"], job_result["jobName"], job_result.get("shareIdentifier", None))
+                        TrainingQueuedJob(job_result["jobArn"], job_result["jobName"], job_result.get("shareIdentifier", None), job_result.get("quotaShareName", None))
                     )
                 else:
                     logging.warning("Missing JobArn or JobName in Batch ListJobs API")
@@ -182,27 +190,35 @@ def list_jobs_by_share(
         self,
         status: Optional[str] = JOB_STATUS_RUNNING,
         share_identifier: Optional[str] = None,
+        quota_share_name: Optional[str] = None,
     ) -> List[TrainingQueuedJob]:
         """List Batch jobs according to status and share.
 
         Args:
             status: Batch job status.
             share_identifier: Batch fairshare share identifier.
+            quota_share_name: Batch quota management share name.
 
         Returns: A list of QueuedJob.
 
         """
         filters = None
+        if share_identifier != None and quota_share_name != None:
+            raise ValueError(
+                "Either share_identifier or quota_share_name can be specified, but not both"
+            )
         if share_identifier:
             filters = [{"name": "SHARE_IDENTIFIER", "values": [share_identifier]}]
+        elif quota_share_name:
+            filters = [{"name": "QUOTA_SHARE_NAME", "values": [quota_share_name]}]
 
         jobs_to_return = []
         next_token = None
         for job_result_dict in _list_service_job(self.queue_name, status, filters, next_token):
             for job_result in job_result_dict.get("jobSummaryList", []):
                 if "jobArn" in job_result and "jobName" in job_result:
                     jobs_to_return.append(
-                        TrainingQueuedJob(job_result["jobArn"], job_result["jobName"], job_result.get("shareIdentifier", None))
+                        TrainingQueuedJob(job_result["jobArn"], job_result["jobName"], job_result.get("shareIdentifier", None), job_result.get("quotaShareName", None))
                     )
                 else:
                     logging.warning("Missing JobArn or JobName in Batch ListJobs API")

sagemaker-train/src/sagemaker/train/aws_batch/training_queued_job.py

@@ -45,10 +45,11 @@ class TrainingQueuedJob:
     With this class, customers are able to attach the latest training job to a ModelTrainer.
     """
 
-    def __init__(self, job_arn: str, job_name: str, share_identifier: Optional[str] = None):
+    def __init__(self, job_arn: str, job_name: str, share_identifier: Optional[str] = None, quota_share_name: Optional[str] = None):
         self.job_arn = job_arn
         self.job_name = job_name
         self.share_identifier = share_identifier
+        self.quota_share_name = quota_share_name
         self._no_training_job_status = {"SUBMITTED", "PENDING", "RUNNABLE"}
 
     def get_model_trainer(self) -> ModelTrainer:

sagemaker-train/tests/unit/train/aws_batch/conftest.py

@@ -43,6 +43,7 @@
 # Batch configuration
 SCHEDULING_PRIORITY = 1
 SHARE_IDENTIFIER = "test-share-id"
+QUOTA_SHARE_NAME = "test-quota-share"
 ATTEMPT_DURATION_IN_SECONDS = 86400
 REASON = "Test termination reason"
 NEXT_TOKEN = "test-next-token"
@@ -159,6 +160,24 @@
     "nextToken": None,
 }
 
+LIST_SERVICE_JOB_BY_QUOTA_SHARE_RESP_WITH_JOBS = {
+    "jobSummaryList": [
+        {
+            "jobName": JOB_NAME,
+            "jobArn": JOB_ARN,
+            "jobId": JOB_ID,
+            "quotaShareName": QUOTA_SHARE_NAME,
+        },
+        {
+            "jobName": "another-job",
+            "jobArn": "arn:aws:batch:us-west-2:123456789012:job/another-id",
+            "jobId": "another-id",
+            "quotaShareName": "another-quota-share",
+        },
+    ],
+    "nextToken": None,
+}
+
 LIST_SERVICE_JOB_RESP_WITH_NEXT_TOKEN = {
     "jobSummaryList": [
         {"jobName": JOB_NAME, "jobArn": JOB_ARN, "jobId": JOB_ID},

sagemaker-train/tests/unit/train/aws_batch/test_batch_api_helper.py

@@ -37,6 +37,7 @@
     TIMEOUT_CONFIG,
     SCHEDULING_PRIORITY,
     SHARE_IDENTIFIER,
+    QUOTA_SHARE_NAME,
     SUBMIT_SERVICE_JOB_RESP,
     DESCRIBE_SERVICE_JOB_RESP_RUNNING,
     LIST_SERVICE_JOB_RESP_EMPTY,
@@ -97,6 +98,25 @@ def test_submit_service_job_with_all_params(self, mock_get_client):
         assert call_kwargs["shareIdentifier"] == SHARE_IDENTIFIER
         assert call_kwargs["timeoutConfig"] == TIMEOUT_CONFIG
 
+    @patch("sagemaker.train.aws_batch.batch_api_helper.get_batch_boto_client")
+    def test_submit_service_job_with_quota_share_name(self, mock_get_client):
+        """Test submit_service_job with quota_share_name parameter"""
+        mock_client = Mock()
+        mock_client.submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP
+        mock_get_client.return_value = mock_client
+
+        result = _submit_service_job(
+            TRAINING_JOB_PAYLOAD,
+            JOB_NAME,
+            JOB_QUEUE,
+            quota_share_name=QUOTA_SHARE_NAME,
+        )
+
+        assert result["jobArn"] == SUBMIT_SERVICE_JOB_RESP["jobArn"]
+        call_kwargs = mock_client.submit_service_job.call_args[1]
+        assert call_kwargs["quotaShareName"] == QUOTA_SHARE_NAME
+        assert "shareIdentifier" not in call_kwargs
+
     @patch("sagemaker.train.aws_batch.batch_api_helper.get_batch_boto_client")
     def test_submit_service_job_with_tags(self, mock_get_client):
         """Test submit_service_job merges batch and training tags"""