azure-pipelines
ncnn
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Name
Complexity
Churn
Issues
A
tools\pnnx\tests\test_torch_squeeze.py
5 1 1
A
src\simplemath.cpp
89 1 1
A
tools\pnnx\tests\test_torch_std.py
6 1 1
A
.github\workflows\ios-simulator-gpu.yml
 3 -
A
tools\pnnx\tests\test_torch_sum.py
5 1 1
A
tools\quantize\imreadwrite.h
17 1 -
A
tools\pnnx\tests\test_vit_b_32.py
3 1 1
A
.github\workflows\android-armv7-gpu.yml
 3 -
A
.github\workflows\codeql-analysis.yml
 2 -
A
.github\workflows\windows-x64-cpu.yml
 3 -
A
python\ncnn\model_zoo\peleenetssd.py
4 1 -
A
src\layer\arm\convolutiondepthwise_3x3.h
17 1 -
A
src\layer\instancenorm.cpp
13 2 -
A
src\layer\vulkan\deconvolution_vulkan.h
0 1 -
A
tools\pnnx\src\pass_ncnn\nn_AdaptiveMaxPool2d.cpp
10 2 -
B
src\layer\x86\convolution_packed_int8.h
333 2 2
B
src\layer\arm\gemm_arm_asimdhp.cpp
465 1 6
B
src\net.cpp
520 5 11
B
src\gpu.cpp
730 4 7
B
tools\ncnnoptimize.cpp
572 1 14