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fix atune-adm analyse failed problem

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Pshysimon
2025-04-12 16:44:11 +08:00
committed by root
parent b96d9b78f0
commit 2cc1896225
1 changed files with 8 additions and 8 deletions
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16
analysis/optimizer/app_characterization.py
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@@ -202,16 +202,9 @@ class AppCharacterization(WorkloadCharacterization):
:param feature_selection: whether to perform feature extraction
:param consider_perf: whether to consider perf indicators
"""
if consider_perf == None:
consider_perf = self.consider_perf
data_features = self.get_consider_perf(consider_perf)
cpu_exist, mem_exist, net_quality_exist, net_io_exist, disk_io_exist = self.bottleneck.search_bottleneck(data)
bottleneck_binary = (int(cpu_exist) << 4) | (int(mem_exist) << 3) | (int(net_quality_exist) << 2) | (int(net_io_exist) << 1) | int(disk_io_exist)
data = data[data_features]
tencoder_path = os.path.join(self.model_path, "tencoder.pkl")
aencoder_path = os.path.join(self.model_path, "aencoder.pkl")
scaler_path = os.path.join(self.model_path, "scaler.pkl")
@@ -226,6 +219,13 @@ class AppCharacterization(WorkloadCharacterization):
type_model_clf = joblib.load(type_model_path)
app_model_clf = joblib.load(app_model_path)
if consider_perf is None:
consider_perf = (len(self.scaler.mean_) == len(data.columns))
data_features = self.get_consider_perf(consider_perf)
data = data[data_features]
data = self.scaler.transform(data)
if feature_selection:
@@ -290,4 +290,4 @@ class AppCharacterization(WorkloadCharacterization):
confidence = prediction[1] / len(result)
if confidence > 0.5:
return bottleneck_binary, prediction[0], confidence
return bottleneck_binary, "default", confidence
return bottleneck_binary, "default", confidence