Tencent/ncnn

master

ncnn

Grade	Name	Complexity	Churn	Issues
F	src\layer\arm\convolution_5x5_pack4_bf16s.h	26	1	118
F	src\layer\arm\convolution_3x3_winograd_bf16s.h	348	1	41
F	src\layer\x86\convolution_3x3_winograd_int8.h	476	2	25
F	src\layer\x86\convolution_im2col_gemm.h	450	3	26
F	src\layer\x86\convolution_3x3_winograd_bf16s.h	540	2	45
F	src\layer\arm\convolution_im2col_gemm.h	201	1	57
F	src\layer\arm\gemm_int8_fp16s.h	740	1	68
D	tools\onnx\onnx2ncnn.cpp	1444	2	16
D	src\layer\arm\convolution_5x5_pack8_fp16s.h	15	1	19
C	src\mat_pixel_drawing_font.h	0	1	14
C	src\layer\x86\slice_x86.cpp	316	2	17
C	.github\workflows\release.yml		5	13
C	src\layer\x86\packing_x86.cpp	259	2	29
C	src\layer\x86\convolution_packed_int8.h	333	2	11
C	src\layer\x86\convolution_im2col_gemm_int8.h	229	2	11
C	src\layer\riscv\gemm_riscv.cpp	423	2	19
C	src\layer\arm\packing_arm.cpp	151	1	20
C	src\gpu.cpp	1143	6	13
B	src\layer\arm\gemm_arm_vfpv4.cpp	188	2	10
B	src\layer\arm\gemm_arm_asimdhp.cpp	479	2	14