Repository: open-compass/opencompass
Issue: [Bug]

### 先决条件

- [x] 我已经搜索过 [问题](https://github.com/open-compass/opencompass/issues/) 和 [讨论](https://github.com/open-compass/opencompass/discussions) 但未得到预期的帮助。
- [x] 错误在 [最新版本](https://github.com/open-compass/opencompass) 中尚未被修复。

### 问题类型

我正在使用官方支持的任务/模型/数据集进行评估。

### 环境

Python3.11

### 重现问题 - 代码/配置示例

from kfp import dsl, compiler
from kfp.dsl import Input, Output, Dataset, Metrics

# 组件1：生成数据
@dsl.component(base_image='kubeflownotebookswg/jupyter-pytorch-full:v1.8.0')
def generate_data_op(output_data: Output[Dataset]):
    import pandas as pd
    import numpy as np
    import os

    df = pd.DataFrame({'x': np.random.rand(100)})
    df['y'] = 3.5 * df['x'] + np.random.normal(0, 0.1, 100)

    # 确保输出目录存在
    os.makedirs(os.path.dirname(output_data.path), exist_ok=True)
    df.to_csv(output_data.path, index=False)
    print(f"Data saved to: {output_data.path}")

# 组件2：训练模型并输出 MAE
@dsl.component(base_image='kubeflownotebookswg/jupyter-pytorch-full:v1.8.0')
def train_model_op(
    input_data: Input[Dataset],
    output_metrics: Output[Metrics]
):
    import pandas as pd
    import torch
    import torch.nn as nn
    import os

    df = pd.read_csv(input_data.path)
    x = torch.tensor(df['x'].values, dtype=torch.float32).view(-1, 1)
    y = torch.tensor(df['y'].values, dtype=torch.float32).view(-1, 1)

    model = nn.Linear(1, 1)
    loss_fn = nn.L1Loss()
    optimizer = torch.optim.SGD(model.parameters(), lr=0.1)

    for epoch in range(100):
        pred = model(x)
        loss = loss_fn(pred, y)
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

    # 确保输出目录存在
    os.makedirs(os.path.dirname(output_metrics.path), exist_ok=True)
    with open(output_metrics.path, 'w') as f:
        f.write(f"Final MAE: {loss.item()}\n")
    print(f"MAE saved to: {output_metrics.path}")

# 组件3：展示结果
@dsl.component(base_image='kubeflownotebookswg/jupyter-pytorch-full:v1.8.0')
def show_result_op(result: Input[Metrics]):
    with open(result.path) as f:
        print("Final MAE Result:")
        print(f.read())

# 组合为Pipeline
@dsl.pipeline(name="ml-linear-regression-pipeline-v2", description="A linear regression ML pipeline with PyTorch")
def ml_pipeline():
    step1 = generate_data_op()
    step2 = train_model_op(input_data=step1.outputs["output_data"])
    step3 = show_result_op(result=step2.outputs["output_metrics"])

# 编译为yaml
if __name__ == '__main__':
    compiler.Compiler().compile(ml_pipeline, 'ml_11.yaml')
run this code,I get ml_11.yaml file,then i upload the ml_11.yaml to pipeline, I create a experiment and a run ,but I get wrong:time="2025-07-11T11:08:57.973Z" level=info msg="capturing logs" argo=true
I0711 11:08:57.999393      40 cache.go:139] Cannot detect ml-pipeline in the same namespace, default to ml-pipeline.kubeflow:8887 as KFP endpoint.
I0711 11:08:57.999454      40 cache.go:116] Connecting to cache endpoint ml-pipeline.kubeflow:8887
I0711 11:08:58.084635      40 launcher_v2.go:150] publish success.
F0711 11:08:58.084680      40 main.go:49] failed to execute component: 
unable to create directory "/minio/mlpipeline/v2/artifacts/ml-linear-regression-pipeline-v2/6959d57b-fbbf-4e32-97ad-84c75787083d/generate-data-op" 
for output artifact "output_data": mkdir /minio: permission denied
time="2025-07-11T11:08:58.975Z" level=info msg="sub-process exited" argo=true error="<nil>"
Error: exit status 1,can you help me how to resolve the problem,kebeflow1.8 kfp=2.4.0,minio=2023.3,python3.11

### 重现问题 - 命令或脚本

on the run page,i click the button 'start' 

### 重现问题 - 错误信息

time="2025-07-11T11:08:57.973Z" level=info msg="capturing logs" argo=true
I0711 11:08:57.999393      40 cache.go:139] Cannot detect ml-pipeline in the same namespace, default to ml-pipeline.kubeflow:8887 as KFP endpoint.
I0711 11:08:57.999454      40 cache.go:116] Connecting to cache endpoint ml-pipeline.kubeflow:8887
I0711 11:08:58.084635      40 launcher_v2.go:150] publish success.
F0711 11:08:58.084680      40 main.go:49] failed to execute component: 
unable to create directory "/minio/mlpipeline/v2/artifacts/ml-linear-regression-pipeline-v2/6959d57b-fbbf-4e32-97ad-84c75787083d/generate-data-op" 
for output artifact "output_data": mkdir /minio: permission denied
time="2025-07-11T11:08:58.975Z" level=info msg="sub-process exited" argo=true error="<nil>"
Error: exit status 1

### 其他信息

_No response_

I think the bug information is not related to OpenCompass, please provide detailed information and feel free to re-open if needed.