azure-pipelines
ncnn
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Complexity
Churn
Issues
A
examples\mobilenetv3ssdlite.cpp
15 1 -
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src\layer\x86\dequantize_x86.h
0 1 -
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src\layer\loongarch\flatten_loongarch.h
0 1 -
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src\layer\x86\dropout_x86.h
0 1 -
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src\layer\arm\gemm_bf16s.h
385 1 4
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src\layer\x86\eltwise_x86.h
0 1 -
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src\layer\loongarch\hardsigmoid_loongarch.h
0 1 -
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src\layer\x86\elu_x86.h
0 1 -
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.github\workflows\linux-x64-gpu-clang-python.yml
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src\layer\x86\hardsigmoid_x86.cpp
10 1 -
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src\layer\x86\groupnorm_x86.h
0 1 -
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src\layer\x86\gridsample_nearest_compute_blob.h
20 1 -
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src\layer\x86\gridsample_compute_blob.h
12 2 -
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.github\workflows\android-armv7-gpu.yml
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.github\workflows\codeql-analysis.yml
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.github\workflows\windows-x64-cpu.yml
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python\ncnn\model_zoo\peleenetssd.py
4 1 -
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src\layer\arm\convolutiondepthwise_3x3.h
17 1 -
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src\layer\instancenorm.cpp
13 2 -
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src\layer\vulkan\deconvolution_vulkan.h
0 1 -