From 696a1b25eb553c14d93aacd7c506773ceadad25c Mon Sep 17 00:00:00 2001 From: Davide Eynard Date: Thu, 14 Nov 2024 17:29:42 +0000 Subject: [PATCH] Removed TODOs --- lumigator/python/mzai/backend/backend/services/jobs.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/lumigator/python/mzai/backend/backend/services/jobs.py b/lumigator/python/mzai/backend/backend/services/jobs.py index 77c5a13d3..bc8f96a32 100644 --- a/lumigator/python/mzai/backend/backend/services/jobs.py +++ b/lumigator/python/mzai/backend/backend/services/jobs.py @@ -29,7 +29,6 @@ class JobService: # set storage path storage_path = f"s3://{ Path(settings.S3_BUCKET) / settings.S3_JOB_RESULTS_PREFIX }/" - # TODO: we can set a different amount of GPUs per type of job job_settings = { JobType.INFERENCE: { "command": settings.INFERENCE_COMMAND, @@ -109,8 +108,6 @@ def _get_job_params(self, job_type: str, record, request: BaseModel) -> dict: # get dataset S3 path from UUID dataset_s3_path = self.data_service.get_dataset_s3_path(request.dataset) - # TODO: the following is currently both eval and inference, but - # will soon be inference only. Make sure we'll move this out if request.model.startswith("oai://"): model_url = settings.OAI_API_URL elif request.model.startswith("mistral://"): @@ -155,8 +152,6 @@ def _get_job_params(self, job_type: str, record, request: BaseModel) -> dict: def create_job(self, request: JobEvalCreate | JobInferenceCreate) -> JobResponse: """Creates a new evaluation workload to run on Ray and returns the response status.""" - # TODO: we might want to explicitly provide a job string definition as a request - # parameter, so we can reuse the same config profiles across different job types if isinstance(request, JobEvalCreate): job_type = JobType.EVALUATION elif isinstance(request, JobInferenceCreate):