truesoni/ncnn

master

ncnn

Grade	Name	Complexity	Churn	Issues
F	src\layer\arm\convolution_3x3_winograd_bf16s.h	348	2	41
F	src\layer\arm\gemm_fp16s.h	385	1	29
F	src\layer\arm\convolution_im2col_gemm_int8.h	323	3	38
F	src\layer\arm\convolution_3x3_winograd_fp16s.h	529	2	22
F	src\layer\arm\convolution_7x7_pack1to4_bf16s.h	15	1	35
F	src\layer\arm\convolution_5x5_pack4.h	16	1	34
F	src\layer\arm\gemm_arm.cpp	778	3	38
F	src\layer\x86\convolution_im2col_gemm_int8.h	419	4	40
F	src\layer\arm\convolution_im2col_gemm.h	201	2	63
F	src\layer\arm\convolution_im2col_gemm_bf16s.h	136	2	48
F	src\layer\arm\convolution_3x3_winograd_int8.h	328	2	23
F	src\layer\arm\convolution_5x5_pack4_bf16s.h	26	1	121
F	src\layer\x86\convolution_3x3_winograd.h	714	2	36
F	src\layer\arm\convolution_3x3_winograd.h	484	2	71
F	src\layer\x86\convolution_3x3_winograd_int8.h	476	3	37
F	src\layer\x86\gemm_x86.cpp	869	3	26
F	src\layer\x86\convolution_packed_int8.h	333	2	15
F	src\layer\riscv\gemm_riscv.cpp	579	2	24
F	src\layer\arm\gemm_bf16s.h	385	1	31
F	src\layer\arm\convolution_5x5_pack8_fp16s.h	15	1	19