Tencent/ncnn

master

ncnn

Grade	Name	Complexity	Churn	Issues
F	src\layer\x86\convolution_3x3_winograd.h	714	3	59
F	src\layer\x86\convolution_3x3_winograd_bf16s.h	540	2	45
F	src\layer\x86\convolution_3x3_winograd_int8.h	476	2	25
A	src\layer\x86\convolution_5x5.h	8	1	3
F	src\layer\x86\convolution_im2col_gemm.h	450	3	26
F	src\layer\x86\convolution_im2col_gemm_bf16s.h	405	4	33
C	src\layer\x86\convolution_im2col_gemm_int8.h	229	2	11
B	src\layer\x86\convolution_packed.h	263	2	16
B	src\layer\x86\convolution_packed_bf16s.h	265	2	15
C	src\layer\x86\convolution_packed_int8.h	333	2	11
B	src\layer\x86\convolution_x86.cpp	569	2	14
A	src\layer\x86\convolution_x86.h	0	2	-
A	src\layer\x86\convolution_x86_avx2.cpp	8	1	-
A	src\layer\x86\convolution_x86_avx512bf16.cpp	13	1	-
A	src\layer\x86\convolution_x86_avx512vnni.cpp	4	1	-
A	src\layer\x86\convolution_x86_avxvnni.cpp	4	1	-
A	src\layer\x86\convolution_x86_avxvnniint8.cpp	1	1	-
A	src\layer\x86\convolution_x86_xop.cpp	3	1	-
A	src\layer\x86\convolutiondepthwise_3x3.h	12	1	1
A	src\layer\x86\convolutiondepthwise_3x3_int8.h	28	1	3