Modify gRPC API with Current Request Number

docs/new-algorithm-service.md

@@ -59,8 +59,8 @@ class HyperoptService(
         trials = Trial.convert(request.trials)
         #--------------------------------------------------------------
         # Your code here
-        # Implement the logic to generate new assignments for the given request number.
-        # For example, if request.request_number is 2, you should return:
+        # Implement the logic to generate new assignments for the given current request number.
+        # For example, if request.current_request_number is 2, you should return:
         # [
         #   [Assignment(name=param-1, value=3),
         #    Assignment(name=param-2, value=cat2),
@@ -73,7 +73,7 @@ class HyperoptService(
         #    Assignment(name=param-4, value=4.32)
         #   ],
         # ]
-        list_of_assignments = your_logic(search_space, trials, request.request_number)
+        list_of_assignments = your_logic(search_space, trials, request.current_request_number)
         #--------------------------------------------------------------
         # Convert list_of_assignments to
         return api_pb2.GetSuggestionsReply(

pkg/apis/manager/v1beta1/api.proto

@@ -288,9 +288,9 @@ message DeleteObservationLogReply {
 
 message GetSuggestionsRequest {
     Experiment experiment = 1;
-    repeated Trial trials = 2; // all completed trials owned by the experiment.
-    int32 request_number = 3; ///The number of Suggestion you request at one time. When you set 3 to request_number, you can get three Suggestions at one time.
-    int32 total_request_number = 4;//The number of Suggestions requested till now
+    repeated Trial trials = 2; // All completed trials owned by the experiment.
+    int32 current_request_number = 3; // The number of Suggestions requested at one time. When you set 3 to current_request_number, you get three Suggestions at one time.
+    int32 total_request_number = 4; // The number of Suggestions requested till now.
 }
 
 message GetSuggestionsReply {

pkg/apis/manager/v1beta1/gen-doc/api.md

@@ -352,9 +352,9 @@ Discrete and Categorical type use List.
 | Field | Type | Label | Description |
 | ----- | ---- | ----- | ----------- |
 | experiment | [Experiment](#api.v1.beta1.Experiment) |  |  |
-| trials | [Trial](#api.v1.beta1.Trial) | repeated | all completed trials owned by the experiment. |
-| request_number | [int32](#int32) |  | The number of Suggestion you request at one time. When you set 3 to request_number, you can get three Suggestions at one time. |
-| total_request_number | [int32](#int32) |  | The number of Suggestions requested till now |
+| trials | [Trial](#api.v1.beta1.Trial) | repeated | All completed trials owned by the experiment. |
+| current_request_number | [int32](#int32) |  | The number of Suggestions requested at one time. When you set 3 to current_request_number, you get three Suggestions at one time. |
+| total_request_number | [int32](#int32) |  | The number of Suggestions requested till now. |
 
 
 

pkg/apis/manager/v1beta1/gen-doc/index.html

@@ -965,21 +965,21 @@ <h3 id="api.v1.beta1.GetSuggestionsRequest">GetSuggestionsRequest</h3>
                   <td>trials</td>
                   <td><a href="#api.v1.beta1.Trial">Trial</a></td>
                   <td>repeated</td>
-                  <td><p>all completed trials owned by the experiment. </p></td>
+                  <td><p>All completed trials owned by the experiment. </p></td>
                 </tr>
 
                 <tr>
-                  <td>request_number</td>
+                  <td>current_request_number</td>
                   <td><a href="#int32">int32</a></td>
                   <td></td>
-                  <td><p>The number of Suggestion you request at one time. When you set 3 to request_number, you can get three Suggestions at one time. </p></td>
+                  <td><p>The number of Suggestions requested at one time. When you set 3 to current_request_number, you get three Suggestions at one time. </p></td>
                 </tr>
 
                 <tr>
                   <td>total_request_number</td>
                   <td><a href="#int32">int32</a></td>
                   <td></td>
-                  <td><p>The number of Suggestions requested till now </p></td>
+                  <td><p>The number of Suggestions requested till now. </p></td>
                 </tr>
 
             </tbody>

pkg/controller.v1beta1/suggestion/suggestionclient/suggestionclient.go

@@ -78,8 +78,8 @@ func (g *General) SyncAssignments(
 	e *experimentsv1beta1.Experiment,
 	ts []trialsv1beta1.Trial) error {
 	logger := log.WithValues("Suggestion", types.NamespacedName{Name: instance.GetName(), Namespace: instance.GetNamespace()})
-	requestNum := int(instance.Spec.Requests) - int(instance.Status.SuggestionCount)
-	if requestNum <= 0 {
+	currentRequestNum := int(instance.Spec.Requests) - int(instance.Status.SuggestionCount)
+	if currentRequestNum <= 0 {
 		return nil
 	}
 
@@ -102,19 +102,19 @@ func (g *General) SyncAssignments(
 		instance.Status.AlgorithmSettings)
 
 	requestSuggestion := &suggestionapi.GetSuggestionsRequest{
-		Experiment:         g.ConvertExperiment(filledE),
-		Trials:             g.ConvertTrials(ts),
-		RequestNumber:      int32(requestNum),
-		TotalRequestNumber: int32(instance.Spec.Requests),
+		Experiment:           g.ConvertExperiment(filledE),
+		Trials:               g.ConvertTrials(ts),
+		CurrentRequestNumber: int32(currentRequestNum),
+		TotalRequestNumber:   int32(instance.Spec.Requests),
 	}
 
 	// Get new suggestions
 	responseSuggestion, err := rpcClientSuggestion.GetSuggestions(ctx, requestSuggestion)
 	if err != nil {
 		return err
 	}
-	logger.Info("Getting suggestions", "endpoint", endpoint, "Number of request parameters", requestNum, "Number of response parameters", len(responseSuggestion.ParameterAssignments))
-	if len(responseSuggestion.ParameterAssignments) != requestNum {
+	logger.Info("Getting suggestions", "endpoint", endpoint, "Number of request parameters", currentRequestNum, "Number of response parameters", len(responseSuggestion.ParameterAssignments))
+	if len(responseSuggestion.ParameterAssignments) != currentRequestNum {
 		err := fmt.Errorf("The response contains unexpected trials")
 		logger.Error(err, "The response contains unexpected trials")
 		return err

pkg/controller.v1beta1/suggestion/suggestionclient/suggestionclient_test.go

@@ -909,7 +909,7 @@ func newFakeRequest() *suggestionapi.GetSuggestionsRequest {
 				},
 			},
 		},
-		RequestNumber:      2,
-		TotalRequestNumber: 6,
+		CurrentRequestNumber: 2,
+		TotalRequestNumber:   6,
 	}
 }

pkg/suggestion/v1beta1/chocolate/base_service.py

@@ -46,9 +46,11 @@ def __init__(self, algorithm_name, search_space):
         self.chocolate_optimizer = None
         self.create_optimizer(algorithm_name)
         # created_trials is the list of dicts with all created trials assignments, loss and trial name
-        # _chocolate_id is the ID of the trial, Assignment names are encoded, _loss is the target metric, _trial_name is the Trial name
+        # _chocolate_id is the ID of the trial, Assignment names are encoded,
+        # _loss is the target metric, _trial_name is the Trial name
         # One row example:
-        # {'_chocolate_id': 0, 'LS1scg==': 0.001, 'LS1udW0tZXBvY2hz': 1, 'LS1udW0tbGF5ZXJz': 2, "_loss": "0.97", "_trial_name": "grid-hsdvfdwl"}
+        # {'_chocolate_id': 0, 'LS1scg==': 0.001, 'LS1udW0tZXBvY2hz': 1, 'LS1udW0tbGF5ZXJz': 2,
+        #   "_loss": "0.97", "_trial_name": "grid-hsdvfdwl"}
         self.created_trials = []
         self.recorded_trials_names = []
 
@@ -103,13 +105,13 @@ def create_optimizer(self, algorithm_name):
             raise Exception(
                 '"Failed to create Chocolate optimizer for the algorithm: {}'.format(algorithm_name))
 
-    def getSuggestions(self, trials, request_number, total_request_number):
+    def getSuggestions(self, trials, current_request_number, total_request_number):
         """
         Get the new suggested trials with chocolate algorithm.
         """
         logger.info("-" * 100 + "\n")
         logger.info("New GetSuggestions call with total requested {} and currently requesting {} \n".format(
-            total_request_number, request_number))
+            total_request_number, current_request_number))
         for _, trial in enumerate(trials):
             if trial.name not in self.recorded_trials_names:
                 loss_for_choco = float(trial.target_metric.value)
@@ -137,8 +139,10 @@ def getSuggestions(self, trials, request_number, total_request_number):
                 i = 0
                 while new_trial_loss_idx == -1 and i < len(self.created_trials):
                     # Created Trial must not include loss and must have the same param assignment
-                    if ((DB_FIELD_LOSS not in self.created_trials[i] or self.created_trials[i][DB_FIELD_LOSS] is None) and
-                            len(trial_assignments_dict.items() & self.created_trials[i].items()) == len(self.search_space.params)):
+                    if ((DB_FIELD_LOSS not in self.created_trials[i] or
+                         self.created_trials[i][DB_FIELD_LOSS] is None) and
+                            len(trial_assignments_dict.items() & self.created_trials[i].items()) ==
+                            len(self.search_space.params)):
                         new_trial_loss_idx = i
                     i += 1
 
@@ -161,12 +165,13 @@ def getSuggestions(self, trials, request_number, total_request_number):
         # Assuming that created_trials are already populated
         # TODO: Handle Restart of algorithm pod
         logger.info("{} Trials created in DB".format(len(self.created_trials)))
-        if total_request_number != len(self.created_trials) + request_number:
+        if total_request_number != len(self.created_trials) + current_request_number:
             logger.info("Mismatch in generated trials with k8s suggestions trials")
         new_actual_requested_no = total_request_number - len(self.created_trials)
-        prev_generated_no = request_number - new_actual_requested_no
-        logger.info("In this call, New {} Trials will be generated, {} Trials will be reused from previously generated".format(
-            new_actual_requested_no, prev_generated_no))
+        prev_generated_no = current_request_number - new_actual_requested_no
+        logger.info(
+            "In this call, New {} Trials will be generated, {} Trials will be reused from previously generated".format(
+                new_actual_requested_no, prev_generated_no))
 
         list_of_assignments = []
         if prev_generated_no > 0:
@@ -199,8 +204,8 @@ def getSuggestions(self, trials, request_number, total_request_number):
                     "Chocolate db is exhausted, increase Search Space or decrease maxTrialCount!")
 
         if len(list_of_assignments) > 0:
-            logger.info(
-                "GetSuggestions returns {} Trials from requested {} Trials\n\n".format(len(list_of_assignments), request_number))
+            logger.info("GetSuggestions returns {} Trials from requested {} Trials\n\n".format(
+                len(list_of_assignments), current_request_number))
 
         return list_of_assignments
 

pkg/suggestion/v1beta1/chocolate/service.py

@@ -84,7 +84,7 @@ def GetSuggestions(self, request, context):
 
         trials = Trial.convert(request.trials)
         new_assignments = self.base_service.getSuggestions(
-            trials, request.request_number, request.total_request_number)
+            trials, request.current_request_number, request.total_request_number)
         return api_pb2.GetSuggestionsReply(
             parameter_assignments=Assignment.generate(new_assignments)
         )

pkg/suggestion/v1beta1/goptuna/service.go

@@ -72,9 +72,9 @@ func (s *SuggestionService) GetSuggestions(
 		return nil, status.Error(codes.Internal, err.Error())
 	}
 
-	requestNumber := int(req.GetRequestNumber())
-	parameterAssignments := make([]*api_v1_beta1.GetSuggestionsReply_ParameterAssignments, requestNumber)
-	for i := 0; i < requestNumber; i++ {
+	currentRequestNumber := int(req.GetCurrentRequestNumber())
+	parameterAssignments := make([]*api_v1_beta1.GetSuggestionsReply_ParameterAssignments, currentRequestNumber)
+	for i := 0; i < currentRequestNumber; i++ {
 		trialID, assignments, err := sampleNextParam(s.study, s.searchSpace)
 		if err != nil {
 			klog.Errorf("Failed to sample next param: trialID=%d, err=%s", trialID, err)

pkg/suggestion/v1beta1/goptuna/service_test.go

@@ -94,7 +94,7 @@ func TestSuggestionService_GetSuggestions(t *testing.T) {
 						ParameterSpecs: parameterSpecs,
 					},
 				},
-				RequestNumber: 2,
+				CurrentRequestNumber: 2,
 			},
 			expectedCode: codes.OK,
 		},
@@ -122,7 +122,7 @@ func TestSuggestionService_GetSuggestions(t *testing.T) {
 						ParameterSpecs: parameterSpecs,
 					},
 				},
-				RequestNumber: 2,
+				CurrentRequestNumber: 2,
 			},
 		},
 		{
@@ -149,7 +149,7 @@ func TestSuggestionService_GetSuggestions(t *testing.T) {
 						ParameterSpecs: parameterSpecs,
 					},
 				},
-				RequestNumber: 2,
+				CurrentRequestNumber: 2,
 			},
 		},
 	} {
@@ -169,8 +169,8 @@ func TestSuggestionService_GetSuggestions(t *testing.T) {
 				return
 			}
 
-			if len(reply.ParameterAssignments) != int(tt.req.RequestNumber) {
-				t.Errorf("GetSuggestions() should return %d suggestions, but got %#v", tt.req.RequestNumber, reply.ParameterAssignments)
+			if len(reply.ParameterAssignments) != int(tt.req.CurrentRequestNumber) {
+				t.Errorf("GetSuggestions() should return %d suggestions, but got %#v", tt.req.CurrentRequestNumber, reply.ParameterAssignments)
 				return
 			}
 

pkg/suggestion/v1beta1/hyperband/service.py

@@ -48,7 +48,7 @@ def GetSuggestions(self, request, context):
                 # Hyperband outlerloop has finished
                 return reply
             # This is a hack to get request number.
-            param.n = request.request_number
+            param.n = request.current_request_number
 
             trials = self._make_bracket(experiment, param)
             for trial in trials:
@@ -212,7 +212,7 @@ def ValidateAlgorithmSettings(self, request, context):
             return self._set_validate_context_error(context, "r_l and resource_name must be set.")
         try:
             rl = float(setting_dict["r_l"])
-        except:
+        except Exception:
             return self._set_validate_context_error(context, "r_l must be a positive float number.")
         else:
             if rl < 0:

pkg/suggestion/v1beta1/hyperopt/base_service.py

@@ -84,7 +84,7 @@ def create_fmin(self):
 
         self.fmin.catch_eval_exceptions = False
 
-    def getSuggestions(self, trials, request_number):
+    def getSuggestions(self, trials, current_request_number):
         """
         Get the new suggested trials with the given algorithm.
         """
@@ -192,8 +192,8 @@ def getSuggestions(self, trials, request_number):
             self.fmin.trials.insert_trial_docs(hyperopt_trials)
             self.fmin.trials.refresh()
 
-        # Produce new request_number ids to make new Suggestion
-        hyperopt_trial_new_ids = self.fmin.trials.new_trial_ids(request_number)
+        # Produce new current_request_number ids to make new Suggestion
+        hyperopt_trial_new_ids = self.fmin.trials.new_trial_ids(current_request_number)
         random_state = self.fmin.rstate.randint(2**31 - 1)
 
         # Trial list that must be deployed
@@ -206,7 +206,7 @@ def getSuggestions(self, trials, request_number):
                 seed=random_state)
         elif self.algorithm_name == TPE_ALGORITHM_NAME:
             # n_startup_jobs indicates for how many Trials we run random suggestion
-            # This must be request_number value
+            # This must be current_request_number value
             # After this tpe suggestion starts analyse Trial info.
             # On the first run we can run suggest just once with n_startup_jobs
             # Next suggest runs must be for each new Trial generation
@@ -216,18 +216,18 @@ def getSuggestions(self, trials, request_number):
                     domain=self.fmin.domain,
                     trials=self.fmin.trials,
                     seed=random_state,
-                    n_startup_jobs=request_number,
+                    n_startup_jobs=current_request_number,
                     **self.algorithm_conf)
                 self.is_first_run = False
             else:
-                for i in range(request_number):
+                for i in range(current_request_number):
                     # hyperopt_algorithm always returns one new Trial
                     new_trials.append(self.hyperopt_algorithm(
                         new_ids=[hyperopt_trial_new_ids[i]],
                         domain=self.fmin.domain,
                         trials=self.fmin.trials,
                         seed=random_state,
-                        n_startup_jobs=request_number,
+                        n_startup_jobs=current_request_number,
                         **self.algorithm_conf)[0])
 
         # Construct return advisor Trials from new hyperopt Trials

pkg/suggestion/v1beta1/hyperopt/service.py

@@ -49,7 +49,7 @@ def GetSuggestions(self, request, context):
             self.is_first_run = False
 
         trials = Trial.convert(request.trials)
-        new_assignments = self.base_service.getSuggestions(trials, request.request_number)
+        new_assignments = self.base_service.getSuggestions(trials, request.current_request_number)
         return api_pb2.GetSuggestionsReply(
             parameter_assignments=Assignment.generate(new_assignments)
         )

pkg/suggestion/v1beta1/nas/darts/service.py

@@ -59,7 +59,7 @@ def GetSuggestions(self, request, context):
             self.is_first_run = False
 
         parameter_assignments = []
-        for i in range(request.request_number):
+        for i in range(request.current_request_number):
 
             self.logger.info(">>> Generate new Darts Trial Job")