feat(dashboard): add training analysis page and improve communication…#31
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feat(dashboard): add training analysis page and improve communication…#31
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…/inference tables
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| # Initialize session state | ||
| if "data_loader" not in st.session_state: | ||
| if "ni" not in st.session_state: |
| if len(selected_runs) == 1: | ||
| st.markdown("#### 📌 核心指标（最新）") | ||
| run = selected_runs[0] | ||
| core = extract_core_metrics(run) |
Collaborator
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extract_core_metrics 这个函数是不用了么？为啥不用了呢，可以考虑保留这个封装；如果确定不要了，记得把这个函数从utils里面删掉
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| except: | ||
| pass |
Collaborator
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这个地方至少得有个error log, 不要直接吞掉exception
| fig = create_gauge_chart( | ||
| duration, | ||
| duration * 2, # Scale to show progress | ||
| duration * 2, |
| init_page("训练测试分析 | InfiniMetrics", "🏋️") | ||
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| def main(): |
Collaborator
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把测试结果数据记得上传test_data分支一份，后续测试dashboard可能用得着，谢谢！ |
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描述：
结果展示：
1.在本地启动 Streamlit 服务：
2.打开浏览器访问 http://localhost:8502 ，点击“训练性能测试分析” 看到新增 training 界面：
