Cambricon / mlu-ops

Efficient operation implementation based on the Cambricon Machine Learning Unit (MLU) .
MIT License
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Logcumsumexp_1.0 #996

Closed shouhoo closed 5 months ago

shouhoo commented 6 months ago

1. Motivation

分享目前为止的工作以供寒武纪方面评审。

2. Modification

改动内容包含logcumsumexp算子的实现,及作为其baseline的测试程序。

3. Test Report

3.1 Modification Details

3.1.1 Accuracy Acceptance Standard

For static threshold standard details, see: [MLU-OPS™ Accuracy Acceptance Standard](https://github.com/Cambricon/mlu-ops/blob/master/docs/MLU-OPS-Accuracy-Acceptance-Standard.md).

3.1.2 Operator Scheme checklist

3.2 Accuracy Test

3.2.1 Accuracy Test

If you have checked the following items, please tick the relevant box.

3.2.2 Parameter Check

Test Point-1: When a new operator is submitted, the test points are given and the test results are stated. Acceptance Standard: Normal error.

Test Point-2: Whether illegal parameters are passed. Acceptance Standard: Normal error.

3.3 Performance Test

3.4 Summary Analysis