added more test cases for hyperopt distributions

Signed-off-by: Shashank Mittal <[email protected]>
kubeflow · Sep 6, 2024 · a444457 · a444457
1 parent b6634e1
commit a444457
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Showing 4 changed files with 28 additions and 9 deletions.
diff --git a/.github/workflows/e2e-test-pytorch-mnist.yaml b/.github/workflows/e2e-test-pytorch-mnist.yaml
@@ -43,4 +43,5 @@ jobs:
           - "grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband"
           - "hyperopt-distribution"
           - "file-metrics-collector,pytorchjob-mnist"
-          - "median-stop-with-json-format,file-metrics-collector-with-json-format"
+          - "median-stop-with-json-format,file-metrics-collector-with-json-format"
+
diff --git a/pkg/suggestion/v1beta1/hyperopt/base_service.py b/pkg/suggestion/v1beta1/hyperopt/base_service.py
@@ -17,14 +17,13 @@
 import hyperopt
 import numpy as np
 
+from pkg.apis.manager.v1beta1.python import api_pb2
 from pkg.suggestion.v1beta1.internal.constant import (
     CATEGORICAL,
     DISCRETE,
     DOUBLE,
     INTEGER,
-    LOG_UNIFORM,
     MAX_GOAL,
-    UNIFORM,
 )
 from pkg.suggestion.v1beta1.internal.trial import Assignment
 
@@ -69,7 +68,7 @@ def create_hyperopt_domain(self):
                     param.name, float(param.min), float(param.max)
                 )
             elif param.type == DOUBLE:
-                if param.distribution == UNIFORM:
+                if param.distribution == api_pb2.UNIFORM or param.distribution is None:
                     if param.step:
                         hyperopt_search_space[param.name] = hyperopt.hp.quniform(
                             param.name,
@@ -81,7 +80,7 @@ def create_hyperopt_domain(self):
                         hyperopt_search_space[param.name] = hyperopt.hp.uniform(
                             param.name, float(param.min), float(param.max)
                         )
-                elif param.distribution == LOG_UNIFORM:
+                elif param.distribution == api_pb2.LOG_UNIFORM:
                     if param.step:
                         hyperopt_search_space[param.name] = hyperopt.hp.qloguniform(
                             param.name,
@@ -93,10 +92,10 @@ def create_hyperopt_domain(self):
                         hyperopt_search_space[param.name] = hyperopt.hp.loguniform(
                             param.name, float(param.min), float(param.max)
                         )
-                else:
-                    hyperopt_search_space[param.name] = hyperopt.hp.uniform(
-                        param.name, float(param.min), float(param.max)
-                    )
+                # else:
+                #     hyperopt_search_space[param.name] = hyperopt.hp.uniform(
+                #         param.name, float(param.min), float(param.max)
+                #     )
             elif param.type == CATEGORICAL or param.type == DISCRETE:
                 hyperopt_search_space[param.name] = hyperopt.hp.choice(
                     param.name, param.list

diff --git a/pkg/suggestion/v1beta1/internal/search_space.py b/pkg/suggestion/v1beta1/internal/search_space.py
@@ -43,6 +43,7 @@ def convert(experiment):
             search_space.goal = constant.MIN_GOAL
         for p in experiment.spec.parameter_specs.parameters:
             search_space.params.append(HyperParameterSearchSpace.convert_parameter(p))
+        print(search_space)
         return search_space
 
     @staticmethod

diff --git a/test/unit/v1beta1/suggestion/test_hyperopt_service.py b/test/unit/v1beta1/suggestion/test_hyperopt_service.py
@@ -183,6 +183,24 @@ def test_get_suggestion(self):
                             parameter_type=api_pb2.DOUBLE,
                             feasible_space=api_pb2.FeasibleSpace(
                                 max="5", min="1", list=[], step="0.5", distribution=api_pb2.LOG_UNIFORM)
+                        ),
+                        api_pb2.ParameterSpec(
+                            name="param-6",
+                            parameter_type=api_pb2.DOUBLE,
+                            feasible_space=api_pb2.FeasibleSpace(
+                                max="5", min="1", list=[], distribution=api_pb2.LOG_UNIFORM)
+                        ),
+                        api_pb2.ParameterSpec(
+                            name="param-7",
+                            parameter_type=api_pb2.DOUBLE,
+                            feasible_space=api_pb2.FeasibleSpace(
+                                max="10", min="5", list=[], step="0.8", distribution=api_pb2.UNIFORM)
+                        ),
+                        api_pb2.ParameterSpec(
+                            name="param-8",
+                            parameter_type=api_pb2.DOUBLE,
+                            feasible_space=api_pb2.FeasibleSpace(
+                                max="10", min="5", list=[], distribution=api_pb2.UNIFORM)
                         )
                     ]
                 )