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

11% duplication:

19,656 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
2,323 duplicated lines

187 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
BigGAN_PyTorch (3%) --> data_utils (8%)	432	11 file pairs	details...
BigGAN_PyTorch (<1%) --> inference (3%)	58	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 187 duplicates...

Size	#	Folders	Files	Lines	Code
45	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	44:91 (8%) 89:136 (8%)	view
39	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	300:346 (7%) 322:368 (7%)	view
38	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	571:615 (7%) 627:671 (6%)	view
34	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	576:614 (6%) 328:367 (6%)	view
34	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGANdeep.py BigGANdeep.py	328:367 (6%) 632:670 (6%)	view
34	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGAN.py	306:345 (6%) 576:614 (6%)	view
34	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	306:345 (6%) 632:670 (6%)	view
31	x 2	BigGAN_PyTorch data_utils	make_hdf5.py make_hdf5.py	139:169 (22%) 257:287 (10%)	view
31	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	470:512 (5%) 534:576 (5%)	view
28	x 2	data_utils data_utils	make_hdf5.py make_hdf5_nns.py	27:54 (9%) 23:50 (19%)	view
27	x 2	BigGAN_PyTorch data_utils	make_hdf5.py make_hdf5.py	60:88 (19%) 106:134 (9%)	view
27	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	92:118 (5%) 138:164 (4%)	view
24	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	183:209 (4%) 212:238 (4%)	view
21	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGAN.py BigGANdeep.py	266:295 (3%) 288:317 (3%)	view
20	x 2	inference inference	sample.py test.py	35:66 (19%) 35:66 (8%)	view
20	x 2	BigGAN_PyTorch data_utils	make_hdf5.py make_hdf5_nns.py	36:55 (14%) 31:50 (13%)	view
20	x 2	BigGAN_PyTorch data_utils	make_hdf5.py make_hdf5.py	36:55 (14%) 35:54 (7%)	view
19	x 2	data_utils data_utils	make_hdf5.py make_hdf5_nns.py	112:130 (6%) 49:67 (13%)	view
19	x 2	BigGAN_PyTorch data_utils	make_hdf5.py make_hdf5_nns.py	66:84 (13%) 49:67 (13%)	view
19	x 2	stylegan2_ada_pytorch stylegan2_ada_pytorch	calc_metrics.py train.py	37:57 (11%) 617:636 (3%)	view

Duplicated Units

The list of top 5 duplicated units.

See data for all 5 unit duplicates...

Size	#	Folders	Files	Lines	Code
19	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGANdeep.py BigGAN.py	0:0 0:0	view
19	x 2	BigGAN_PyTorch BigGAN_PyTorch	BigGANdeep.py BigGAN.py	0:0 0:0	view
13	x 2	BigGAN_PyTorch/TFHub BigGAN_PyTorch/TFHub	biggan_v1.py biggan_v1.py	0:0 0:0	view
7	x 2	stylegan2_ada_pytorch stylegan2_ada_pytorch	style_mixing.py generate.py	0:0 0:0	view
7	x 2	data_utils BigGAN_PyTorch	utils.py utils.py	0:0 0:0	view