Merge branch 'main' of github.com:oracle/accelerated-data-science into feature/ms_backup_retention

Author: iamishaan

.github/workflows/run-forecast-unit-tests.yml

@@ -27,7 +27,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.9", "3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v4

.github/workflows/run-operators-unit-tests.yml

@@ -27,7 +27,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v4

THIRD_PARTY_LICENSES.txt

@@ -483,6 +483,11 @@ rrcf
 * Source code: https://github.com/kLabUM/rrcf
 * Project home: https://github.com/kLabUM/rrcf
 
+Merlion
+* Copyright 2021 Salesforce.com Inc
+* License: BSD-3 Clause License
+* Source code: https://github.com/salesforce/Merlion
+* Project Home: https://github.com/salesforce/Merlion
 
 =============================== Licenses ===============================
 ------------------------------------------------------------------------

ads/aqua/common/utils.py

@@ -1071,7 +1071,6 @@ def list_hf_models(query: str) -> List[str]:
     try:
         models = HfApi().list_models(
             model_name=query,
-            task="text-generation",
             sort="downloads",
             direction=-1,
             limit=20,

ads/aqua/config/config.py

@@ -40,6 +40,7 @@ def get_finetuning_config_defaults():
             "VM.GPU.A10.2": {"batch_size": 1, "replica": "1-10"},
             "BM.GPU.A10.4": {"batch_size": 1, "replica": 1},
             "BM.GPU4.8": {"batch_size": 4, "replica": 1},
+            "BM.GPU.L40S-NC.4": {"batch_size": 4, "replica": 1},
             "BM.GPU.A100-v2.8": {"batch_size": 6, "replica": 1},
             "BM.GPU.H100.8": {"batch_size": 6, "replica": 1},
         }

ads/aqua/config/deployment_config_defaults.json

@@ -30,6 +30,7 @@
     "VM.GPU.A10.2",
     "BM.GPU.A10.4",
     "BM.GPU4.8",
+    "BM.GPU.L40S-NC.4",
     "BM.GPU.A100-v2.8",
     "BM.GPU.H100.8",
     "VM.Standard.A1.Flex"

ads/aqua/config/evaluation/evaluation_service_config.py

@@ -224,6 +224,7 @@ def search_shapes(
 
     class Config:
         extra = "ignore"
+        protected_namespaces = ()
 
 
 class EvaluationServiceConfig(Serializable):

ads/aqua/config/resource_limit_names.json

@@ -2,6 +2,7 @@
   "BM.GPU.A10.4": "ds-gpu-a10-count",
   "BM.GPU.A100-v2.8": "ds-gpu-a100-v2-count",
   "BM.GPU.H100.8": "ds-gpu-h100-count",
+  "BM.GPU.L40S-NC.4": "ds-gpu-l40s-nc-count",
   "BM.GPU4.8": "ds-gpu4-count",
   "VM.GPU.A10.1": "ds-gpu-a10-count",
   "VM.GPU.A10.2": "ds-gpu-a10-count"

ads/aqua/extension/deployment_handler.py

@@ -102,6 +102,7 @@ def post(self, *args, **kwargs):
         ocpus = input_data.get("ocpus")
         memory_in_gbs = input_data.get("memory_in_gbs")
         model_file = input_data.get("model_file")
+        private_endpoint_id = input_data.get("private_endpoint_id")
 
         self.finish(
             AquaDeploymentApp().create(
@@ -124,6 +125,7 @@ def post(self, *args, **kwargs):
                 ocpus=ocpus,
                 memory_in_gbs=memory_in_gbs,
                 model_file=model_file,
+                private_endpoint_id=private_endpoint_id,
             )
         )
 

ads/aqua/extension/model_handler.py

@@ -13,7 +13,6 @@
 from ads.aqua.extension.base_handler import AquaAPIhandler
 from ads.aqua.extension.errors import Errors
 from ads.aqua.model import AquaModelApp
-from ads.aqua.model.constants import ModelTask
 from ads.aqua.model.entities import AquaModelSummary, HFModelSummary
 from ads.aqua.ui import ModelFormat
 
@@ -68,7 +67,7 @@ def read(self, model_id):
         return self.finish(AquaModelApp().get(model_id))
 
     @handle_exceptions
-    def delete(self):
+    def delete(self, id=""):
         """Handles DELETE request for clearing cache"""
         url_parse = urlparse(self.request.path)
         paths = url_parse.path.strip("/")
@@ -177,10 +176,8 @@ def _find_matching_aqua_model(model_id: str) -> Optional[AquaModelSummary]:
 
         return None
 
-
-
     @handle_exceptions
-    def get(self,*args, **kwargs):
+    def get(self, *args, **kwargs):
         """
         Finds a list of matching models from hugging face based on query string provided from users.
 
@@ -194,13 +191,11 @@ def get(self,*args, **kwargs):
             Returns the matching model ids string
         """
 
-        query=self.get_argument("query",default=None)
+        query = self.get_argument("query", default=None)
         if not query:
-            raise HTTPError(400,Errors.MISSING_REQUIRED_PARAMETER.format("query"))
-        models=list_hf_models(query)
-        return self.finish({"models":models})
-
-
+            raise HTTPError(400, Errors.MISSING_REQUIRED_PARAMETER.format("query"))
+        models = list_hf_models(query)
+        return self.finish({"models": models})
 
     @handle_exceptions
     def post(self, *args, **kwargs):
@@ -234,16 +229,17 @@ def post(self, *args, **kwargs):
                 "Please verify the model's status on the Hugging Face Model Hub or select a different model."
             )
 
-        # Check pipeline_tag, it should be `text-generation`
-        if (
-            not hf_model_info.pipeline_tag
-            or hf_model_info.pipeline_tag.lower() != ModelTask.TEXT_GENERATION
-        ):
-            raise AquaRuntimeError(
-                f"Unsupported pipeline tag for the chosen model: '{hf_model_info.pipeline_tag}'. "
-                f"AQUA currently supports the following tasks only: {', '.join(ModelTask.values())}. "
-                "Please select a model with a compatible pipeline tag."
-            )
+        # Commented the validation below to let users to register any model type.
+        # # Check pipeline_tag, it should be `text-generation`
+        # if not (
+        #     hf_model_info.pipeline_tag
+        #     and hf_model_info.pipeline_tag.lower() in ModelTask
+        # ):
+        #     raise AquaRuntimeError(
+        #         f"Unsupported pipeline tag for the chosen model: '{hf_model_info.pipeline_tag}'. "
+        #         f"AQUA currently supports the following tasks only: {', '.join(ModelTask.values())}. "
+        #         "Please select a model with a compatible pipeline tag."
+        #     )
 
         # Check if it is a service/verified model
         aqua_model_info: AquaModelSummary = self._find_matching_aqua_model(