Use camelCase consistently in study job spec

examples/bayseopt-example.yaml

@@ -8,25 +8,25 @@ metadata:
 spec:
   studyName: random-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-accuracy
-  optimizationgoal: 0.99
-  requestcount: 10
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-accuracy
+  optimizationGoal: 0.99
+  requestCount: 10
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.03"
     - name: --num-layers
-      parametertype: int
+      parameterType: int
       feasible:
         min: "1"
         max: "4"
     - name: --optimizer
-      parametertype: categorical
+      parameterType: categorical
       feasible:
         list:
         - sgd

examples/gpu-example.yaml

@@ -8,24 +8,24 @@ metadata:
 spec:
   studyName: gpu-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-accuracy
-  optimizationgoal: 0.99
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-accuracy
+  optimizationGoal: 0.99
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.03"
     - name: --num-layers
-      parametertype: int
+      parameterType: int
       feasible:
         min: "2"
         max: "3"
     - name: --optimizer
-      parametertype: categorical
+      parameterType: categorical
       feasible:
         list:
         - sgd

examples/grid-example.yaml

@@ -8,24 +8,24 @@ metadata:
 spec:
   studyName: grid-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-accuracy
-  optimizationgoal: 0.99
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-accuracy
+  optimizationGoal: 0.99
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.03"
     - name: --num-layers
-      parametertype: int
+      parameterType: int
       feasible:
         min: "2"
         max: "5"
     - name: --optimizer
-      parametertype: categorical
+      parameterType: categorical
       feasible:
         list:
         - sgd

examples/hypb-example.yaml

@@ -8,30 +8,30 @@ metadata:
 spec:
   studyName: hypb-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-accuracy
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-accuracy
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.03"
     - name: --num-layers
-      parametertype: int
+      parameterType: int
       feasible:
         min: "2"
         max: "5"
     - name: --optimizer
-      parametertype: categorical
+      parameterType: categorical
       feasible:
         list:
         - sgd
         - adam
         - ftrl
     - name: --num-epochs
-      parametertype: int
+      parameterType: int
       feasible:
         min: "20"
         max: "20"

examples/nasjob-example-RL.yaml

@@ -8,11 +8,11 @@ metadata:
 spec:
   studyName: nas-rl-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-Accuracy
-  optimizationgoal: 0.99
-  requestcount: 3
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-Accuracy
+  optimizationGoal: 0.99
+  requestCount: 3
+  metricsNames:
     - accuracy
   nasConfig:
     graphConfig:
@@ -25,16 +25,16 @@ spec:
         - 10
     operations:
       - operationType: convolution
-        parameterconfigs:
+        parameterConfigs:
           - name: filter_size
-            parametertype: categorical
+            parameterType: categorical
             feasible:
               list:
               - "3"
               - "5"
               - "7"
           - name: num_filter
-            parametertype: categorical
+            parameterType: categorical
             feasible:
               list:
               - "32"
@@ -43,21 +43,21 @@ spec:
               - "96"
               - "128"
           - name: stride
-            parametertype: categorical
+            parameterType: categorical
             feasible:
               list:
               - "1"
               - "2"
       - operationType: reduction
-        parameterconfigs:
+        parameterConfigs:
           - name: reduction_type
-            parametertype: categorical
+            parameterType: categorical
             feasible:
               list:
               - max_pooling
               - avg_pooling
           - name: pool_size
-            parametertype: int
+            parameterType: int
             feasible:
               min: "2"
               max: "3"

examples/pytorchjob-example.yaml

@@ -8,20 +8,20 @@ metadata:
 spec:
   studyName: pytorchjob-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: accuracy
-  optimizationgoal: 0.99
-  requestcount: 4
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: accuracy
+  optimizationGoal: 0.99
+  requestCount: 4
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.05"
     - name: --momentum
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.5"
         max: "0.9"

examples/random-example.yaml

@@ -8,25 +8,25 @@ metadata:
 spec:
   studyName: random-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: Validation-accuracy
-  optimizationgoal: 0.99
-  requestcount: 4
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: Validation-accuracy
+  optimizationGoal: 0.99
+  requestCount: 4
+  metricsNames:
     - accuracy
-  parameterconfigs:
+  parameterConfigs:
     - name: --lr
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.03"
     - name: --num-layers
-      parametertype: int
+      parameterType: int
       feasible:
         min: "2"
         max: "5"
     - name: --optimizer
-      parametertype: categorical
+      parameterType: categorical
       feasible:
         list:
         - sgd

examples/tf-event_test.yaml

@@ -8,22 +8,22 @@ metadata:
 spec:
   studyName: random-example-long-test
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: test/accuracy
-  optimizationgoal: 0.99
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: test/accuracy
+  optimizationGoal: 0.99
+  metricsNames:
     - train/accuracy
     - train/cross_entropy
     - test/accuracy
     - test/cross_entropy
-  parameterconfigs:
+  parameterConfigs:
     - name: --learning_rate
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.001"
         max: "0.01"
     - name: --dropout
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.7"
         max: "0.9"

examples/tfjob-example.yaml

@@ -8,20 +8,20 @@ metadata:
 spec:
   studyName: tfjob-example
   owner: crd
-  optimizationtype: maximize
-  objectivevaluename: accuracy_1
-  optimizationgoal: 0.99
-  requestcount: 4
-  metricsnames:
+  optimizationType: maximize
+  objectiveValueName: accuracy_1
+  optimizationGoal: 0.99
+  requestCount: 4
+  metricsNames:
     - accuracy_1
-  parameterconfigs:
+  parameterConfigs:
     - name: --learning_rate
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.01"
         max: "0.05"
     - name: --batch_size
-      parametertype: int
+      parameterType: int
       feasible:
         min: "100"
         max: "200"

examples/xgboost-bayesian-example.yaml

@@ -9,19 +9,19 @@ metadata:
 spec:
   studyName: xgboost-example
   owner: crd
-  optimizationtype: minimize
-  objectivevaluename: mean_absolute_error
-  optimizationgoal: 10000
-  requestcount: 10
+  optimizationType: minimize
+  objectiveValueName: mean_absolute_error
+  optimizationGoal: 10000
+  requestCount: 10
 
-  parameterconfigs:
+  parameterConfigs:
     - name: --learning-rate
-      parametertype: double
+      parameterType: double
       feasible:
         min: "0.05"
         max: "0.15"
     - name: --n-estimators
-      parametertype: int
+      parameterType: int
       feasible:
         min: "10000"
         max: "30000"