Tencent/ncnn

master

ncnn

Grade	Name	Complexity	Churn	Issues
B	src\layer\x86\binaryop_x86.cpp	257	3	11
B	src\layer\x86\concat_x86.cpp	234	2	11
B	src\layer\x86\convolution1d_packed.h	256	2	12
B	src\layer\x86\convolution1d_packed_bf16s.h	258	2	11
B	src\layer\x86\convolution_3x3_pack1to4.h	33	1	8
B	src\layer\x86\convolution_3x3_pack1to8.h	34	1	9
B	src\layer\x86\convolution_packed.h	263	2	16
B	src\layer\x86\convolution_packed_bf16s.h	265	2	15
B	src\layer\x86\convolution_x86.cpp	569	2	14
B	src\layer\x86\convolutiondepthwise_x86.cpp	297	1	9
B	src\layer\x86\interp_bf16s.h	164	1	12
B	src\layer\x86\lstm_x86.cpp	114	1	9
B	src\layer\mips\convolution_mips.cpp	437	1	9
B	src\layer\arm\lstm_arm.cpp	212	1	13
B	src\layer\mips\convolution_sgemm.h	43	1	7
B	src\layer\mips\convolution_sgemm_int8.h	66	1	13
B	src\layer\x86\reshape_x86.cpp	172	2	6
B	src\layer\mips\convolutiondepthwise_mips.cpp	169	1	9
B	src\layer\mips\deconvolution_mips.cpp	65	1	10
B	src\mat_pixel.cpp	269	1	13