Commit df3952a2 authored by suiguoxin's avatar suiguoxin
Browse files

fix val err

parent dbac6edb
authorName: default authorName: default
experimentName: example_auto-gbdt experimentName: example_auto-gbdt
trialConcurrency: 1 trialConcurrency: 1
maxExecDuration: 10h maxExecDuration: 48h
maxTrialNum: 10 maxTrialNum: 1000
#choice: local, remote, pai #choice: local, remote, pai
trainingServicePlatform: local trainingServicePlatform: local
searchSpacePath: search_space.json searchSpacePath: search_space.json
...@@ -11,10 +11,11 @@ useAnnotation: false ...@@ -11,10 +11,11 @@ useAnnotation: false
tuner: tuner:
#choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner
#SMAC (SMAC should be installed through nnictl) #SMAC (SMAC should be installed through nnictl)
builtinTunerName: TPE builtinTunerName: GPTuner
classArgs: classArgs:
#choice: maximize, minimize #choice: maximize, minimize
optimize_mode: minimize optimize_mode: minimize
cold_start_num : 1
trial: trial:
command: python3 main.py command: python3 main.py
codeDir: . codeDir: .
......
...@@ -11,10 +11,11 @@ useAnnotation: false ...@@ -11,10 +11,11 @@ useAnnotation: false
tuner: tuner:
#choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
#SMAC (SMAC should be installed through nnictl) #SMAC (SMAC should be installed through nnictl)
builtinTunerName: TPE builtinTunerName: GPTuner
classArgs: classArgs:
#choice: maximize, minimize #choice: maximize, minimize
optimize_mode: maximize optimize_mode: maximize
cold_start_num : 1
trial: trial:
command: python3 mnist.py command: python3 mnist.py
codeDir: . codeDir: .
......
...@@ -40,7 +40,7 @@ def _match_val_type(vals, bounds): ...@@ -40,7 +40,7 @@ def _match_val_type(vals, bounds):
vals_new.append( vals_new.append(
min(bounds[i]['_value'], key=lambda x: abs(x - vals[i]))) min(bounds[i]['_value'], key=lambda x: abs(x - vals[i])))
elif _type in ['quniform', 'randint']: elif _type in ['quniform', 'randint']:
vals_new.append(np.around(bounds[i]['_value'])) vals_new.append(np.around(vals[i]))
else: else:
vals_new.append(vals[i]) vals_new.append(vals[i])
......
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