Adding more endpoint options

src/backend/inference_endpoint.py

@@ -20,8 +20,33 @@ def create_endpoint(endpoint_name, repository, framework="pytorch", task="text-g
         logger.debug("Hit the following exception:")
         logger.debug(e)
         logger.debug("Attempting to continue.")
-        endpoint = get_inference_endpoint(endpoint_name)
-        endpoint.update(repository=repository, framework=framework, task=task, accelerator=accelerator,  instance_size=instance_size, instance_type=instance_type)
+        try:
+            endpoint = get_inference_endpoint(endpoint_name)
+            endpoint.update(repository=repository, framework=framework, task=task, accelerator=accelerator,  instance_size=instance_size, instance_type=instance_type)
+        except:
+            if instance_type == "nvidia-l4":
+                # Try a larger, different, more expensive GPU.
+                endpoint = create_inference_endpoint(endpoint_name,
+                                                     repository=repository,
+                                                     framework=framework, task=task,
+                                                     accelerator=accelerator,
+                                                     vendor=vendor, region=region,
+                                                     type=type,
+                                                     instance_size="x1",
+                                                     instance_type="nvidia-a100")
+            elif instance_type == "a100" and instance_size == "x1":
+                endpoint = create_inference_endpoint(endpoint_name,
+                                                     repository=repository,
+                                                     framework=framework, task=task,
+                                                     accelerator=accelerator,
+                                                     vendor=vendor, region=region,
+                                                     type=type,
+                                                     instance_size="x4",
+                                                     instance_type="nvidia-a10g")
+            else:
+                logger.info("Getting expensive to run this model without human oversight. Exiting.")
+                sys.exit()
+
     endpoint.fetch()
     logger.info("Endpoint status: %s." % (endpoint.status))
     if endpoint.status == "scaledToZero":