make predict work

Author: Ziqun Ye

ads/opctl/backend/ads_model_deployment.py

@@ -178,26 +178,27 @@ def watch(self) -> None:
     def predict(self) -> None:
         ocid = self.config["execution"].get("ocid")
         data = self.config["execution"].get("data")
-        if "datasciencemodeldeployment" in ocid:
-            with AuthContext(auth=self.auth_type, profile=self.profile):
-                model_deployment = ModelDeployment.from_id(ocid)
-                return model_deployment.predict(data)
-        elif "datasciencemodel":
-            with AuthContext(auth=self.auth_type, profile=self.profile):
-                import tempfile
-                with tempfile.TemporaryDirectory() as td:
-
-                    model = GenericModel.from_model_catalog(ocid, artifact_dir=os.path.join(td, str(uuid.uuid4())), force_overwrite=True)
+        # if "datasciencemodeldeployment" in ocid:
+        with AuthContext(auth=self.auth_type, profile=self.profile):
+            model_deployment = ModelDeployment.from_id(ocid)
+            data = json.loads(data)
+            print(model_deployment.predict(data))
+        # elif "datasciencemodel":
+        #     with AuthContext(auth=self.auth_type, profile=self.profile):
+        #         import tempfile
+        #         with tempfile.TemporaryDirectory() as td:
+
+        #             model = GenericModel.from_model_catalog(ocid, artifact_dir=os.path.join(td, str(uuid.uuid4())), force_overwrite=True)
 
-                    conda_pack = self.config["execution"].get("conda", None)
-                    if not conda_pack and hasattr(model.metadata_custom, "EnvironmentType") and model.metadata_custom.EnvironmentType == "published" and hasattr(model.metadata_custom, "CondaEnvironmentPath"):
-                        conda_pack = model.metadata_custom.CondaEnvironmentPath
-                    if conda_pack and "service-conda-packs" not in conda_pack:
-                        print("install conda pack and activate the conda pack.")
+        #             conda_pack = self.config["execution"].get("conda", None)
+        #             if not conda_pack and hasattr(model.metadata_custom, "EnvironmentType") and model.metadata_custom.EnvironmentType == "published" and hasattr(model.metadata_custom, "CondaEnvironmentPath"):
+        #                 conda_pack = model.metadata_custom.CondaEnvironmentPath
+        #             if conda_pack and "service-conda-packs" not in conda_pack:
+        #                 print("install conda pack and activate the conda pack.")
 
-                    data = json.loads(data)
-                    print(model.verify(data))
-        else:
-            raise ValueError("Only model ocid or model deployment ocid is supported.")
+        #             data = json.loads(data)
+        #             print(model.verify(data))
+        # else:
+        #     raise ValueError("Only model ocid or model deployment ocid is supported.")
 
 

ads/opctl/backend/local.py

@@ -653,5 +653,20 @@ def predict(self) -> None:
                 f"Run with the --debug argument to view container logs."
             )
 
+    def _run_with_image(self, bind_volumes):
+        ocid = self.config["execution"].get("ocid")
+        data = self.config["execution"].get("data")
+        image = self.config["execution"].get("image")
+        env_vars = self.config["execution"]["env_vars"]
+        # compartment_id = self.config["execution"].get("compartment_id", self.config["infrastructure"].get("compartment_id"))
+        # project_id = self.config["execution"].get("project_id", self.config["infrastructure"].get("project_id"))
+        entrypoint = self.config["execution"].get("entrypoint", None)
+        command = self.config["execution"].get("command", None)
+        if self.config["execution"].get("source_folder", None):
+            bind_volumes.update(self._mount_source_folder_if_exists(bind_volumes))
+        bind_volumes.update(self.config["execution"]["volumes"])
+        
+        return run_container(image, bind_volumes, env_vars, command, entrypoint)
+    
     def _run_with_local_env(self, ):
         pass

ads/opctl/cli.py

@@ -503,23 +503,14 @@ def deactivate(**kwargs):
 @commands.command()
 @click.argument("ocid", nargs=1)
 @click.argument("data", nargs=1)
-@click.argument("conda_slug", nargs=1)
+@click.argument("conda_slug", nargs=1, required=False)
 @add_options(_options)
 def predict(**kwargs):
     """
     Deactivates a data science service.
     """
     suppress_traceback(kwargs["debug"])(predict_cmd)(**kwargs)
 
-   
-@commands.command()
-@click.argument("conda", nargs=1)
-@click.argument("ocid", nargs=1)
-@click.argument("data", nargs=1)
-@add_options(_options)
-def verify(**kwargs):
-    suppress_traceback(kwargs["debug"])(verify_cmd)(**kwargs)
-
 
 commands.add_command(ads.opctl.conda.cli.commands)
 commands.add_command(ads.opctl.spark.cli.commands)

ads/opctl/cmds.py

@@ -484,8 +484,8 @@ def predict(**kwargs):
         #         p.config["execution"]["backend"] = b.value
 
     # return _BackendFactory(p.config).backend.predict()
-
     if "datasciencemodeldeployment" in p.config["execution"].get("ocid", ""):
+        
         return ModelDeploymentBackend(p.config).predict()
     elif "datasciencemodel" in p.config["execution"].get("ocid", ""):
         return LocalModelDeploymentBackend(p.config).predict()

ads/opctl/script.py

@@ -0,0 +1,26 @@
+import json
+import os
+import sys
+import tempfile
+import uuid
+
+from ads.model.generic_model import GenericModel
+
+
+def verify(ocid, data, compartment_id, project_id):
+    with tempfile.TemporaryDirectory() as td:
+        model = GenericModel.from_model_catalog(ocid,
+                                                artifact_dir=os.path.join(td, str(uuid.uuid4())),
+                                                force_overwrite=True, compartment_id=compartment_id, project_id=project_id)
+        data = json.loads(data)
+        print(model.verify(data, auto_serialize_data=False))
+
+
+def main():
+    args = sys.argv[1:]
+    verify(ocid = args[0], data=args[1], compartment_id=args[2], project_id=args[3])
+    return 0
+
+
+if __name__ == "__main__":
+    main()