Cambricon / mlu-ops

Efficient operation implementation based on the Cambricon Machine Learning Unit (MLU) .
MIT License
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[Feature](mluOpGenerateProposalsV2): check nan/inf state and reconstruct && perf box decode #1011

Closed mahxn0 closed 6 months ago

mahxn0 commented 6 months ago

Thanks for your contribution and we appreciate it a lot. :rocket::rocket:

  1. Motivation

check nan/inf state and reconstruct && perf box decode

  1. Modification

modified: kernels/generate_proposals_v2/generate_proposals_v2.cpp modified: kernels/generate_proposals_v2/generate_proposals_v2.h new file: kernels/generate_proposals_v2/generate_proposals_v2_nms_utils.h new file: kernels/generate_proposals_v2/generate_proposals_v2_union1_590.mlu new file: kernels/generate_proposals_v2/generate_proposals_v2_union_default.mlu

3. Test Report

If you want to know how to do operator testing, you can see GTest-User-Guide-zh.

3.1 Modification Details

3.1.1 Accuracy Acceptance Standard

For static threshold standard details, see: MLU-OPS™ Accuracy Acceptance Standard.

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.

Please fill your test results(Error Message) in here, ...

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

Test results...

3.3 Performance Test

See MLU-OPS™ Performance Acceptance Standard for details.

Platform:MLU370

# The test results should contain Op name, Shape, Data type,  
#   MLU Hardware Time(us), MLU Interface Time(us), MLU IO Efficiency, 
#   MLU Compute Efficiency, and Mlu Workspace Size(Bytes)
# 
# for example:
#
# ----------- case0 -----------
# case0
# [Op name                ]: abs
# [Shape                  ]: input.shape=[1024,1024,3,4], output.shape=[1024,1024,3,4]
# [Data type]             ]: float32
# [MLU Hardware Time      ]: 15728 (us)
# [MLU Interface Time     ]: 369.008 (us)
# [MLU IO Efficiency      ]: 0.23275
# [MLU Compute Efficiency ]: 0.5
# [Mlu Workspace Size     ]: -1 (Bytes)
# 
# ----------- case1 -----------
# ...

Platform:MLU590

# ----------- case0 -----------
# ----------- case1 -----------
# ...

3.4 Summary Analysis

Please give a brief overview here, if you want to note and summarize the content.