alibaba / TinyNeuralNetwork

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

13% duplication:

44,430 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
5,880 duplicated lines

9,636 duplicates

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

Duplication per Extension

Duplication per Component (primary)

Longest Duplicates

The list of 50 longest duplicates.

See data for all 9,636 duplicates...

Size	#	Folders	Files	Lines	Code
90	x 2	models models	efficientnet_v2_l.py efficientnet_v2_xl.py	696:786 (4%) 894:984 (3%)	view
71	x 2	models models	efficientnet_v2_l.py efficientnet_v2_xl.py	115:185 (3%) 103:173 (2%)	view
48	x 2	models models	efficientnet_v2_l.py efficientnet_v2_xl.py	9:57 (2%) 9:57 (1%)	view
45	x 2	tinynn/graph/quantization tinynn/graph/quantization	quantizer.py quantizer.py	847:896 (1%) 3730:3779 (1%)	view
38	x 2	tinynn/graph tinynn/graph	modifier.py modifier.py	1728:1778 (1%) 2159:2207 (1%)	view
35	x 2	tinynn/converter/operators/torch tinynn/converter/operators/torch	aten.py aten.py	3221:3261 (1%) 3283:3323 (1%)	view
34	x 2	tinynn/graph/quantization tinynn/graph/quantization	qat_modules.py qat_modules.py	210:248 (6%) 321:359 (6%)	view
34	x 2	models models	efficientnet_v2_l.py efficientnet_v2_xl.py	801:834 (1%) 999:1032 (1%)	view
31	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	3490:3524 (<1%) 3699:3733 (<1%)	view
31	x 2	models models	efficientnet_v2_s.py efficientnet_v2_xl.py	323:353 (2%) 263:293 (1%)	view
30	x 2	tinynn/converter/operators/torch tinynn/converter/operators/torch	aten.py aten.py	2859:2897 (<1%) 2907:2945 (<1%)	view
29	x 2	tutorials/pruning tutorials/quantization	basic.ipynb basic.ipynb	278:306 (9%) 409:437 (6%)	view
28	x 2	models models	efficientnet_v2_m.py efficientnet_v2_s.py	507:535 (1%) 355:383 (2%)	view
27	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	50:80 (<1%) 354:384 (<1%)	view
27	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	50:80 (<1%) 506:536 (<1%)	view
27	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	354:384 (<1%) 506:536 (<1%)	view
27	x 2	tinynn/graph/quantization tinynn/graph/quantization	qat_modules.py qat_modules.py	178:207 (4%) 289:318 (4%)	view
25	x 2	tinynn/converter/operators/torch tinynn/converter/operators/torch	aten.py aten.py	2587:2612 (<1%) 3410:3435 (<1%)	view
24	x 2	tinynn/converter/operators tinynn/converter/operators	optimize.py optimize.py	752:783 (<1%) 790:821 (<1%)	view
21	x 2	models models	efficientnet_v2_l.py efficientnet_v2_xl.py	65:85 (<1%) 65:85 (<1%)	view
21	x 2	tinynn/converter/operators tinynn/converter/operators	optimize.py optimize.py	2749:2780 (<1%) 2844:2875 (<1%)	view
20	x 2	tutorials/model_conversion tutorials/pruning	basic.ipynb basic.ipynb	182:201 (9%) 287:306 (6%)	view
20	x 2	tutorials/model_conversion tutorials/quantization	basic.ipynb basic.ipynb	182:201 (9%) 418:437 (4%)	view
20	x 2	models models	efficientnet_v2_m.py efficientnet_v2_xl.py	584:603 (1%) 972:991 (<1%)	view
20	x 2	tinynn/graph/quantization tinynn/graph/quantization	qat_modules.py qat_modules.py	157:176 (3%) 268:287 (3%)	view
20	x 2	models models	efficientnet_v2_s.py efficientnet_v2_xl.py	418:437 (1%) 958:977 (<1%)	view
20	x 2	models models	efficientnet_v2_l.py efficientnet_v2_s.py	760:779 (<1%) 418:437 (1%)	view
19	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	3830:3852 (<1%) 3885:3907 (<1%)	view
19	x 2	tinynn/graph/quantization tinynn/graph/quantization	quantizer.py quantizer.py	1487:1508 (<1%) 2748:2769 (<1%)	view
19	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	3830:3852 (<1%) 3913:3935 (<1%)	view
19	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	3885:3907 (<1%) 3913:3935 (<1%)	view
18	x 2	tinynn/graph tinynn/graph	modifier.py modifier.py	1905:1922 (<1%) 2033:2050 (<1%)	view
18	x 2	tinynn/converter/operators tinynn/converter/operators	optimize.py optimize.py	1880:1899 (<1%) 2212:2231 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2378:2398 (<1%) 3661:3681 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2012:2032 (<1%) 3661:3681 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2186:2206 (<1%) 2378:2398 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2186:2206 (<1%) 2432:2452 (<1%)	view
17	x 2	tinynn/converter/operators/torch tinynn/converter/operators/torch	aten.py aten.py	747:770 (<1%) 817:840 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	1091:1111 (<1%) 2378:2398 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	1091:1111 (<1%) 2432:2452 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2160:2180 (<1%) 2432:2452 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2160:2180 (<1%) 2186:2206 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2160:2180 (<1%) 2378:2398 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	1091:1111 (<1%) 2012:2032 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	1091:1111 (<1%) 2160:2180 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	1091:1111 (<1%) 2186:2206 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2378:2398 (<1%) 2432:2452 (<1%)	view
17	x 2	tinynn/graph/quantization tinynn/util	quantizer.py quantization_analysis_util.py	3078:3100 (<1%) 96:117 (7%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2432:2452 (<1%) 3661:3681 (<1%)	view
17	x 2	tinynn/converter/operators/tflite tinynn/converter/operators/tflite	generated_ops.py generated_ops.py	2012:2032 (<1%) 2160:2180 (<1%)	view