[HWORKS-349] Add compatibility with 3.0 backend (#166)

* [HWORKS-349] Add compatibility with 3.0 backend
* [HWORKS-349] (2) fix missing value for model_framework
* [HWORKS-349] (3) fix missing deployment status conditions

Author: javierdlrm

python/hsml/engine/serving_engine.py

@@ -93,14 +93,15 @@ def start(self, deployment_instance, await_status: int) -> bool:
         )
 
         if not done:
-            total_steps = (
-                len(self.START_STEPS) - 1
-            ) + self._get_min_starting_instances(deployment_instance)
-            pbar = tqdm(total=total_steps)
+            min_instances = self._get_min_starting_instances(deployment_instance)
+            num_steps = (len(self.START_STEPS) - 1) + min_instances
+            if deployment_instance._predictor._state.condition is None:
+                num_steps = min_instances  # backward compatibility
+            pbar = tqdm(total=num_steps)
             pbar.set_description("Creating deployment")
 
             # set progress function
-            def update_progress(state, num_instances=0):
+            def update_progress(state, num_instances):
                 (progress, desc) = self._get_starting_progress(
                     pbar.n, state, num_instances
                 )
@@ -109,7 +110,7 @@ def update_progress(state, num_instances=0):
                     pbar.set_description(desc)
 
             try:
-                update_progress(state)
+                update_progress(state, num_instances=0)
                 self._serving_api.post(
                     deployment_instance, DEPLOYMENT.ACTION_START
                 )  # start deployment
@@ -138,19 +139,22 @@ def stop(self, deployment_instance, await_status: int) -> bool:
                 if deployment_instance.requested_instances >= num_instances
                 else num_instances
             )
+            if deployment_instance._predictor._state.condition is None:
+                # backward compatibility
+                num_steps = self._get_min_starting_instances(deployment_instance)
             pbar = tqdm(total=num_steps)
             pbar.set_description("Preparing to stop deployment")
 
             # set progress function
-            def update_progress(state, num_instances=0):
+            def update_progress(state, num_instances):
                 (progress, desc) = self._get_stopping_progress(
                     pbar.total, pbar.n, state, num_instances
                 )
                 pbar.update(progress)
                 if desc is not None:
                     pbar.set_description(desc)
 
-            update_progress(state)
+            update_progress(state, num_instances)
             self._serving_api.post(
                 deployment_instance, DEPLOYMENT.ACTION_STOP
             )  # stop deployment
@@ -225,17 +229,25 @@ def _check_status(self, deployment_instance, desired_status):
                 print("Deployment is already stopping")
                 return (True, state)
             if state.status == PREDICTOR_STATE.STATUS_STARTING:
-                raise ModelServingException(
-                    "Deployment is starting, please wait until it completely starts"
-                )
+                if state.condition is not None:
+                    raise ModelServingException(
+                        "Deployment is starting, please wait until it completely starts"
+                    )
             if state.status == PREDICTOR_STATE.STATUS_UPDATING:
-                raise ModelServingException(
-                    "Deployment is updating, please wait until the update completes"
-                )
+                if state.condition is not None:
+                    raise ModelServingException(
+                        "Deployment is updating, please wait until the update completes"
+                    )
 
         return (False, state)
 
     def _get_starting_progress(self, current_step, state, num_instances):
+        if state.condition is None:  # backward compatibility
+            progress = num_instances - current_step
+            if state.status == PREDICTOR_STATE.STATUS_RUNNING:
+                return (progress, "Deployment is ready")
+            return (progress, None if current_step == 0 else "Deployment is starting")
+
         step = self.START_STEPS.index(state.condition.type)
         if (
             state.condition.type == PREDICTOR_STATE.CONDITION_TYPE_STARTED
@@ -253,6 +265,15 @@ def _get_starting_progress(self, current_step, state, num_instances):
         return (progress, desc)
 
     def _get_stopping_progress(self, total_steps, current_step, state, num_instances):
+        if state.condition is None:  # backward compatibility
+            progress = (total_steps - num_instances) - current_step
+            if state.status == PREDICTOR_STATE.STATUS_STOPPED:
+                return (progress, "Deployment is stopped")
+            return (
+                progress,
+                None if total_steps == current_step else "Deployment is stopping",
+            )
+
         step = 0
         if state.condition.type == PREDICTOR_STATE.CONDITION_TYPE_SCHEDULED:
             step = 1 if state.condition.status is None else 0

python/hsml/model.py

@@ -165,6 +165,8 @@ def from_response_json(cls, json_dict):
 
     def update_from_response_json(self, json_dict):
         json_decamelized = humps.decamelize(json_dict)
+        if "type" in json_decamelized:  # backwards compatibility
+            _ = json_decamelized.pop("type")
         self.__init__(**json_decamelized)
         return self
 

python/hsml/predictor.py

@@ -210,7 +210,11 @@ def extract_fields_from_json(cls, json_decamelized):
         )
         kwargs["model_path"] = json_decamelized.pop("model_path")
         kwargs["model_version"] = json_decamelized.pop("model_version")
-        kwargs["model_framework"] = json_decamelized.pop("model_framework")
+        kwargs["model_framework"] = (
+            json_decamelized.pop("model_framework")
+            if "model_framework" in json_decamelized
+            else MODEL.FRAMEWORK_SKLEARN  # backward compatibility
+        )
         kwargs["artifact_version"] = util.extract_field_from_json(
             json_decamelized, "artifact_version"
         )

python/hsml/python/model.py

@@ -66,5 +66,7 @@ def __init__(
 
     def update_from_response_json(self, json_dict):
         json_decamelized = humps.decamelize(json_dict)
+        if "type" in json_decamelized:  # backwards compatibility
+            _ = json_decamelized.pop("type")
         self.__init__(**json_decamelized)
         return self

python/hsml/sklearn/model.py

@@ -66,5 +66,7 @@ def __init__(
 
     def update_from_response_json(self, json_dict):
         json_decamelized = humps.decamelize(json_dict)
+        if "type" in json_decamelized:  # backwards compatibility
+            _ = json_decamelized.pop("type")
         self.__init__(**json_decamelized)
         return self

python/hsml/tensorflow/model.py

@@ -66,5 +66,7 @@ def __init__(
 
     def update_from_response_json(self, json_dict):
         json_decamelized = humps.decamelize(json_dict)
+        if "type" in json_decamelized:  # backwards compatibility
+            _ = json_decamelized.pop("type")
         self.__init__(**json_decamelized)
         return self

python/hsml/torch/model.py

@@ -66,5 +66,7 @@ def __init__(
 
     def update_from_response_json(self, json_dict):
         json_decamelized = humps.decamelize(json_dict)
+        if "type" in json_decamelized:  # backwards compatibility
+            _ = json_decamelized.pop("type")
         self.__init__(**json_decamelized)
         return self

python/hsml/util.py

@@ -108,6 +108,8 @@ def _is_numpy_scalar(x):
 
 def set_model_class(model):
     _ = model.pop("href")
+    if "type" in model:  # backwards compatibility
+        _ = model.pop("type")
 
     if "framework" not in model:
         return BaseModel(**model)