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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

18% duplication:

24,308 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
4,535 duplicated lines

533 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
keras/layers (2%) --> keras/legacy (13%)	281	4 file pairs	details...
keras/engine (<1%) --> keras (1%)	50	2 file pairs	details...

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Longest Duplicates

The list of 20 longest duplicates.

See data for all 533 duplicates...

Size	#	Folders	Files	Lines	Code
45	x 2	keras/layers keras/layers	convolutional_recurrent.py recurrent.py	994:1052 (6%) 2211:2269 (3%)	view
38	x 2	keras/engine keras/engine	training_generator.py training_generator.py	290:330 (9%) 395:435 (9%)	view
36	x 2	keras/layers keras/layers	recurrent.py recurrent.py	1093:1139 (2%) 1674:1720 (2%)	view
29	x 2	keras/backend keras/backend	theano_backend.py theano_backend.py	2228:2258 (1%) 2285:2315 (1%)	view
27	x 2	keras/layers keras/layers	recurrent.py recurrent.py	1690:1724 (1%) 2239:2273 (1%)	view
26	x 2	keras/layers keras/legacy	recurrent.py layers.py	596:623 (1%) 553:580 (5%)	view
26	x 2	keras/layers keras/layers	convolutional.py convolutional.py	793:820 (2%) 1069:1095 (2%)	view
25	x 2	keras/layers keras/layers	convolutional_recurrent.py recurrent.py	1022:1054 (3%) 1109:1141 (1%)	view
25	x 2	keras/layers keras/layers	recurrent.py recurrent.py	1658:1690 (1%) 2203:2235 (1%)	view
25	x 2	keras_mxnet_ci keras_mxnet_ci	nightly-buildspec-python3.yml pr-buildspec-python3.yml	11:36 (73%) 13:38 (69%)	view
24	x 2	benchmark/scripts/models benchmark/scripts/models	lstm_synthetic.py lstm_text_generation.py	67:98 (35%) 91:122 (20%)	view
24	x 2	keras/layers keras/layers	recurrent.py recurrent.py	1109:1139 (1%) 2239:2269 (1%)	view
24	x 2	keras/layers keras/layers	convolutional_recurrent.py recurrent.py	1022:1052 (3%) 1690:1720 (1%)	view
22	x 2	keras/layers keras/layers	convolutional_recurrent.py convolutional_recurrent.py	755:776 (3%) 1054:1075 (3%)	view
20	x 2	keras/layers keras/layers	convolutional.py convolutional.py	1546:1565 (1%) 1687:1706 (1%)	view
20	x 2	keras/backend keras/backend	tensorflow_backend.py theano_backend.py	4356:4430 (1%) 2799:2824 (1%)	view
19	x 2	keras/layers keras/layers	convolutional_recurrent.py recurrent.py	994:1018 (2%) 1666:1690 (1%)	view
18	x 2	keras/layers keras/legacy	recurrent.py layers.py	678:696 (1%) 607:625 (4%)	view
18	x 2	keras/layers keras/layers	recurrent.py recurrent.py	1144:1161 (1%) 1735:1752 (1%)	view
17	x 2	keras/layers keras/layers	convolutional_recurrent.py recurrent.py	1061:1077 (2%) 2277:2293 (1%)	view

Duplicated Units

The list of top 6 duplicated units.

See data for all 6 unit duplicates...

Size	#	Folders	Files	Lines	Code
14	x 2	keras/backend keras/backend	mxnet_backend.py mxnet_backend.py	0:0 0:0	view
8	x 2	keras/legacy keras/layers	layers.py recurrent.py	0:0 0:0	view
8	x 2	keras/backend keras/backend	mxnet_backend.py mxnet_backend.py	0:0 0:0	view
6	x 2	keras/layers keras/layers	pooling.py pooling.py	0:0 0:0	view
38	x 2	keras/backend keras/backend	tensorflow_backend.py theano_backend.py	0:0 0:0	view
14	x 2	keras/backend keras/backend	mxnet_backend.py tensorflow_backend.py	0:0 0:0	view