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Weekly issue metrics report - 2025-04-01..2025-04-07 #31

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Description

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Issue Metrics

Metric Average Median 90th percentile
Time to first response 1 day, 6:30:46 5:05:25 3 days, 0:26:40
Time to close 9 days, 20:24:54 7 days, 3:53:56 20 days, 13:46:50
Time to answer None None None
Time spent in module: android 18 days, 5:50:59 20 days, 23:57:08 22 days, 22:13:57
Time spent in module: ios None None None
Time spent in module: benchmark None None None
Time spent in module: build/install 26 days, 18:20:04 26 days, 18:20:04 26 days, 18:20:04
Time spent in module: vulkan None None None
Time spent in module: llm None None None
Time spent in module: ci 4 days, 0:00:09 4 days, 0:00:09 4 days, 0:00:09
Time spent in module: training None None None
Time spent in module: user experience None None None
Metric Count
Number of items that remain open 19
Number of items closed 6
Number of most active mentors 0
Total number of items created 25
Title URL Author Time to first response Time to close Time to answer Time spent in module: android Time spent in module: ios Time spent in module: benchmark Time spent in module: build/install Time spent in module: vulkan Time spent in module: llm Time spent in module: ci Time spent in module: training Time spent in module: user experience
Check tensor's dim order ambiguity in IR verifier pytorch/executorch#9942 Gasoonjia 0:03:23 None None None None None None None None None None None
torchao not installed by default for ExecuTorch 0.6 RC pytorch/executorch#9940 mergennachin None 1 day, 0:16:47 None None None None None None None None None None
The contiguity of input tensors is lost when copied for the Method::execute in executorch runtime pytorch/executorch#9930 JoshuaGhost 5:44:50 None None None None None None None None None None None
Spelling problem in doc backends-xnnpack.md pytorch/executorch#9924 zxc503 1 day, 5:50:29 2 days, 14:51:04 None None None None None None None None None None
[Android] Better logging on error pytorch/executorch#9921 kirklandsign None None None 23 days, 9:48:09.095617 None None None None None None None None
Update buck version when there's an April 4 or newer release & clean up after pytorch#9890 pytorch/executorch#9919 swolchok None None None None None None None None None None None None
Improve contributor documentation for Android pytorch/executorch#9913 GregoryComer 4:19:39 10 days, 7:47:40 None 10 days, 7:47:40 None None None None None None None None
Support BFloat16 dtype in Android Tensor API pytorch/executorch#9881 GregoryComer 4:26:00 20 days, 23:57:08 None 20 days, 23:57:08 None None None None None None None None
UNSTABLE trunk / test-qnn-model (fp32) pytorch/executorch#9878 kirklandsign 1 day, 3:33:41 4 days, 0:00:12 None None None None None None None 4 days, 0:00:09 None None
[ExecuTorch] recognizes and warns user when Q/DQ ops are not lowered pytorch/executorch#9858 metascroy None None None None None None None None None None None None
[torchao] Enable new quant primitives in PT2E pytorch/executorch#9857 metascroy None None None None None None None None None None None None
[torchao] Migrate exact copy of PT2E from torch.ao to torchao pytorch/executorch#9856 metascroy None None None None None None None None None None None None
[XNNPACK] partitioner recognizes new torchao quant primitives pytorch/executorch#9855 metascroy None None None None None None None None None None None None
[QNN] partitioner recognizes new torchao quant primitives pytorch/executorch#9854 metascroy None None None None None None None None None None None None
[CoreML] partitioner recognizes new torchao quant primitives pytorch/executorch#9853 metascroy None None None None None None None None None None None None
Make ExecuTorch Q/DQ representation default and resilient pytorch/executorch#9852 metascroy None None None None None None None None None None None None
Use eager mode quantize_ with QDQLayout for non-delegated quantized ops in ExecuTorch pytorch/executorch#9851 metascroy None None None None None None None None None None None None
Migrate PT2E to torchao using the new quant primitives pytorch/executorch#9850 metascroy None None None None None None None None None None None None
Standardize ExecuTorch backends on new torchao primitives pytorch/executorch#9849 metascroy None None None None None None None None None None None None
[torchao] support codebook/LUT in torchao pytorch/executorch#9848 metascroy None None None None None None None None None None None None
[CoreML] quantizer supports 4-bit affine (groupwise and channelwise) pytorch/executorch#9847 metascroy None None None None None None None None None None None None
[XNNPACK] support 8d4w in PT2E flow pytorch/executorch#9846 metascroy None None None None None None None None None None None None
[0.6 Release] Quality testing pytorch/executorch#9837 metascroy 7 days, 3:51:05 20 days, 3:36:33 None None None None None None None None None None
Upgrade QNN support to latest version pytorch/executorch#9806 RemonComputer None None None None None None None None None None None None
Support CoreML export on Linux pytorch/executorch#9800 jathu 0:17:03 None None None None None 26 days, 18:20:03.675284 None None None None None

This report was generated with the Issue Metrics Action
Search query used to find these items: repo:pytorch/executorch is:issue created:2025-04-01..2025-04-07

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