model.predict_proba is not working in scoring script for classification

**This is run function. But My output of test data is class only not probabilities.**
@input_schema('data', PandasParameterType(input_sample))
@output_schema(NumpyParameterType(output_sample))
def run(data):
result=model.predict_proba(data)
return result.tolist()

**My deployement Function for reference**
deployment = ManagedOnlineDeployment(
name=deployment_name,
endpoint_name=online_endpoint_name,
model=registered_model.id,
instance_type="Standard_F4s_v2",
instance_count=1,
code_configuration=CodeConfiguration(
code="./artifact_downloads/outputs",
scoring_script="scoring_script.py",
),
liveness_probe=ProbeSettings(
failure_threshold=30,
success_threshold=1,
timeout=2,
period=10,
initial_delay=2000,
),
readiness_probe=ProbeSettings(
failure_threshold=10,
success_threshold=1,
timeout=10,
period=10,
initial_delay=2000,
),
)

从 scoring_script.py 开始，尤其检查 run 函数及其输入/输出 schema，然后检查 ManagedOnlineDeployment CodeConfiguration。使用所示的 model.predict_proba 调用重现已部署的请求，并将其响应与本地结果进行比较。当已部署 scoring 的响应包含类别概率，而不仅仅是类别标签时，即表示完成。

由索引模型根据 Issue 内容生成。