G

Intro

For duplication, we look at places in code where there are 6 or more lines of code that are exactly the same.
Before duplication is calculated, the code is cleaned to remove empty lines, comments, and frequently duplicated constructs such as imports.
You should aim at having as little as possible (<5%) of duplicated code as high-level of duplication can lead to maintenance difficulties, poor factoring, and logical contradictions.

Learn more...

Duplication Overall

46% duplication:

7,796 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
3,598 duplicated lines

481 duplicates

Duplication per Extension

Duplication per Component (primary)

Duplication Between Components (50+ lines)

Download: SVG DOT (open online Graphviz editor)

From Component --> To Component	Duplicated Lines	File Pairs	Details
configs/benchmark_tasks (37%) --> configs/legacy_tasks (49%)	754	73 file pairs	details...
extra_scripts (3%) --> self_supervision_benchmark/utils (7%)	76	3 file pairs	details...

Open 3D force graph...

Show more details on duplication between components...

Longest Duplicates

The list of 20 longest duplicates.

See data for all 481 duplicates...

Size	#	Folders	Files	Lines	Code
39	x 2	configs/benchmark_tasks/...lassification/places205 configs/legacy_tasks/imagenet_linear_tune	resnet50_jigsaw_finetune_linear.yaml resnet50_jigsaw_finetune_linear.yaml	8:49 (84%) 8:49 (84%)	view
35	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	resnet_colorize_finetune_linear.py resnet_supervised_finetune_linear.py	62:96 (12%) 56:90 (12%)	view
35	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/jigsaw	resnet_colorize_finetune_linear.py resnet_jigsaw_finetune_linear.py	144:178 (12%) 139:173 (12%)	view
31	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	resnet_colorize_finetune_linear.py resnet_supervised_finetune_linear.py	213:245 (11%) 204:236 (11%)	view
31	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	resnet_colorize_finetune_linear.py resnet_supervised_finetune_linear.py	137:169 (11%) 127:160 (11%)	view
31	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	resnet_jigsaw_finetune_linear.py resnet_supervised_finetune_linear.py	103:133 (10%) 98:128 (11%)	view
30	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	resnet_jigsaw_finetune_linear.py resnet_supervised_finetune_linear.py	179:208 (10%) 173:202 (11%)	view
30	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	resnet_jigsaw_finetune_linear.py resnet_supervised_finetune_linear.py	219:248 (10%) 211:240 (11%)	view
30	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	alexnet_colorize_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	237:266 (11%) 205:234 (14%)	view
30	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	alexnet_colorize_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	51:80 (11%) 41:70 (14%)	view
30	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	alexnet_colorize_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	145:174 (11%) 127:156 (14%)	view
30	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	alexnet_colorize_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	191:220 (11%) 166:195 (14%)	view
29	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	alexnet_jigsaw_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	249:279 (9%) 168:198 (13%)	view
29	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	alexnet_jigsaw_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	202:232 (9%) 129:159 (13%)	view
29	x 2	configs/benchmark_tasks/...lassification/places205 configs/legacy_tasks/imagenet_linear_tune	resnet50_colorization_finetune_linear... resnet50_colorization_finetune_linear...	19:50 (61%) 19:50 (61%)	view
28	x 2	self_supervision_benchmark/modeling/jigsaw self_supervision_benchmark/modeling/supervised	alexnet_jigsaw_finetune_linear.py caffenet_bvlc_supervised_finetune_lin...	45:72 (8%) 43:70 (13%)	view
28	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/jigsaw	alexnet_colorize_finetune_linear.py alexnet_jigsaw_finetune_linear.py	239:266 (10%) 296:324 (8%)	view
28	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/jigsaw	alexnet_colorize_finetune_linear.py alexnet_jigsaw_finetune_linear.py	193:220 (10%) 249:276 (8%)	view
28	x 2	configs/benchmark_tasks/...lassification/places205 configs/legacy_tasks/imagenet_linear_tune	alexnet_jigsaw_finetune_linear.yaml alexnet_jigsaw_finetune_linear.yaml	16:46 (65%) 16:46 (65%)	view
28	x 2	self_supervision_benchmark/modeling/colorization self_supervision_benchmark/modeling/supervised	resnet_colorize_finetune_linear.py resnet_supervised_finetune_linear.py	100:129 (10%) 92:121 (10%)	view

Duplicated Units

The list of top 3 duplicated units.

See data for all 3 unit duplicates...

Size	#	Folders	Files	Lines	Code
8	x 2	extra_scripts extra_scripts	create_voc_low_shot_challenge_samples.py create_voc_low_shot_samples.py	0:0 0:0	view
8	x 2	extra_scripts self_supervision_benchmark/utils	generate_colorization_bins_priors.py helpers.py	0:0 0:0	view
6	x 2	extra_scripts extra_scripts	pickle_pytorch_to_caffe2.py pickle_caffe2_to_pytorch.py	0:0 0:0	view