alibaba / imood - Duplication

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.

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Duplication Overall

17% duplication:

2,425 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
416 duplicated lines

22 duplicates

dependency graphs: 2D graph | 3D graph | 3D graph (with duplicates)...

Duplication per Extension

Duplication per Component (primary)

Longest Duplicates

The list of 22 longest duplicates.

See data for all 22 duplicates...

Size	#	Folders	Files	Lines	Code
32	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	171:207 (9%) 107:143 (14%)	view
20	x 2	utils utils	common.py common.py	41:60 (9%) 164:183 (9%)	view
15	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	130:148 (4%) 86:104 (6%)	view
15	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	311:325 (4%) 229:243 (6%)	view
15	x 2	datasets datasets	ClassAwareSampler.py ClassPrioritySampler.py	24:43 (33%) 14:33 (4%)	view
13	x 2	utils utils	common.py common.py	27:39 (6%) 150:162 (6%)	view
12	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	270:281 (3%) 200:211 (5%)	view
9	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	328:338 (2%) 247:257 (4%)	view
9	x 2	models models	feat_pool.py feat_pool.py	136:148 (6%) 156:168 (6%)	view
9	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	94:107 (2%) 61:74 (4%)	view
9	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	297:305 (2%) 216:224 (4%)	view
8	x 2	utils utils	common.py common.py	106:113 (3%) 128:135 (3%)	view
8	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	459:468 (2%) 334:343 (3%)	view
8	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	357:364 (2%) 266:273 (3%)	view
7	x 2	utils utils	ltr_metrics.py ltr_metrics.py	123:130 (8%) 140:147 (8%)	view
7	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	45:51 (2%) 21:27 (3%)	view
6	x 2	utils utils	common.py common.py	30:35 (2%) 45:50 (2%)	view
6	x 2	datasets datasets	ClassPrioritySampler.py MixedPrioritizedSampler.py	433:439 (1%) 310:316 (2%)	view
6	x 2	datasets/ImageNet_LT datasets/ImageNet_LT	select_extra_imagenet_1k.py select_ood_test_imagenet_1k.py	4:10 (22%) 4:10 (24%)	view
6	x 2	utils utils	common.py common.py	45:50 (2%) 153:158 (2%)	view
6	x 2	utils utils	common.py common.py	153:158 (2%) 168:173 (2%)	view
6	x 2	utils utils	common.py common.py	30:35 (2%) 168:173 (2%)	view