Fix typo in suggestion packages (#1138)

kubeflow · Apr 13, 2020 · e5bae59 · e5bae59
1 parent 298b8c3
commit e5bae59
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Showing 5 changed files with 6 additions and 6 deletions.
diff --git a/ROADMAP.md b/ROADMAP.md
@@ -22,7 +22,7 @@
 - Delete Suggestion deployment after Experiment is finished [#1061](https://github.com/kubeflow/katib/issues/1061)
 - Save Suggestion state after deployment is deleted [#1062](https://github.com/kubeflow/katib/issues/1062)
 - Reconsider the design of Trial Template [#906](https://github.com/kubeflow/katib/issues/906)
-- Add validation for algortihms (a.k.a suggestions) [#1126](https://github.com/kubeflow/katib/issues/1126)
+- Add validation for algorithms (a.k.a suggestions) [#1126](https://github.com/kubeflow/katib/issues/1126)
 
 ### Neural Architecture Search
 

diff --git a/pkg/suggestion/v1alpha3/chocolate_service.py b/pkg/suggestion/v1alpha3/chocolate_service.py
@@ -39,13 +39,13 @@ def GetSuggestions(self, request, context):
         if self.is_first_run:
             search_space = HyperParameterSearchSpace.convert(
                 request.experiment)
-            self.base_serice = BaseChocolateService(
+            self.base_service = BaseChocolateService(
                 algorithm_name=request.experiment.spec.algorithm.algorithm_name,
                 search_space=search_space)
             self.is_first_run = False
 
         trials = Trial.convert(request.trials)
-        new_assignments = self.base_serice.getSuggestions(
+        new_assignments = self.base_service.getSuggestions(
             trials, request.request_number)
         return api_pb2.GetSuggestionsReply(
             parameter_assignments=Assignment.generate(new_assignments)

diff --git a/pkg/suggestion/v1alpha3/hyperopt/base_hyperopt_service.py b/pkg/suggestion/v1alpha3/hyperopt/base_hyperopt_service.py
@@ -22,7 +22,7 @@ def __init__(self, algorithm_name=TPE_ALGORITHM_NAME, random_state=None, search_
         # elif algorithm_name == 'hyperopt-mix':
         #     self.hyperopt_algorithm = hyperopt.mix.suggest
         else:
-            raise Exception('"Failed to create the algortihm: {}'.format(algorithm_name))
+            raise Exception('"Failed to create the algorithm: {}'.format(algorithm_name))
 
         self.search_space = search_space
         # New hyperopt variables

diff --git a/pkg/suggestion/v1alpha3/internal/search_space.py b/pkg/suggestion/v1alpha3/internal/search_space.py
@@ -39,7 +39,7 @@ def convertParameter(p):
         if p.parameter_type == api.INT:
             # Default value for INT parameter step is 1
             step = 1
-            if p.feasible_space.step != None and p.feasible_space.step != "":
+            if p.feasible_space.step is not None and p.feasible_space.step != "":
                 step = p.feasible_space.step
             return HyperParameter.int(p.name, p.feasible_space.min, p.feasible_space.max, step)
         elif p.parameter_type == api.DOUBLE:

diff --git a/pkg/suggestion/v1alpha3/skopt_service.py b/pkg/suggestion/v1alpha3/skopt_service.py
@@ -25,7 +25,7 @@ def GetSuggestions(self, request, context):
         algorithm_name, config = OptimizerConfiguration.convertAlgorithmSpec(
             request.experiment.spec.algorithm)
         if algorithm_name != "bayesianoptimization":
-            raise Exception("Failed to create the algortihm: {}".format(algorithm_name))
+            raise Exception("Failed to create the algorithm: {}".format(algorithm_name))
 
         if self.is_first_run:
             search_space = HyperParameterSearchSpace.convert(request.experiment)