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@TBD1 TBD1 commented Jan 29, 2026

Motivation

1.修复FD多模download feature不兼容链路二维list的问题
2.增加bos download feature模块log信息

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Usage or Command

Accuracy Tests

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  • Add at least a tag in the PR title.
    • Tag list: [[FDConfig],[APIServer],[Engine], [Scheduler], [PD Disaggregation], [Executor], [Graph Optimization], [Speculative Decoding], [RL], [Models], [Quantization], [Loader], [OP], [KVCache], [DataProcessor], [BugFix], [Docs], [CI], [Optimization], [Feature], [Benchmark], [Others], [XPU], [HPU], [GCU], [DCU], [Iluvatar], [Metax]]
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  • Format your code, run pre-commit before commit.
  • Add unit tests. Please write the reason in this PR if no unit tests.
  • Provide accuracy results.
  • If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

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paddle-bot bot commented Jan 29, 2026

Thanks for your contribution!

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codecov-commenter commented Jan 29, 2026

Codecov Report

❌ Patch coverage is 57.14286% with 6 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (develop@c4abb01). Learn more about missing BASE report.

Files with missing lines Patch % Lines
fastdeploy/utils.py 28.57% 3 Missing and 2 partials ⚠️
fastdeploy/engine/sched/resource_manager_v1.py 85.71% 0 Missing and 1 partial ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             develop    #6276   +/-   ##
==========================================
  Coverage           ?   68.13%           
==========================================
  Files              ?      388           
  Lines              ?    51770           
  Branches           ?     8061           
==========================================
  Hits               ?    35275           
  Misses             ?    13931           
  Partials           ?     2564           
Flag Coverage Δ
GPU 68.13% <57.14%> (?)

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feature_info = f"type=paddle.Tensor, shape={feature.shape}, dtype={feature.dtype}"
elif isinstance(feature, np.ndarray):
feature_info = f"type=np.ndarray, shape={feature.shape}, dtype={feature.dtype}"
else:
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音频场景这里拿到的 feature 是一个list,直接 feature.shape 会报错,可以再加一个list,打印一下长度


try:
if isinstance(link, list) and len(link) > 0:
link = link[0]
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视频每个 link 只会有一个url嘛?

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1131行会循环从bos_links取url下载,目前暂定匹配list[list[str], list[str], ...]这种形式

else:
feature_info = f"type={type(feature).__name__}"

llm_logger.info(f"request {request.request_id} async download feature success: {feature_info}")
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这里是不是可以再加一个计时,打印一下这条请求下载feature共耗时多少

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可以的

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4 participants