huggingface / open-muse
File Size

The distribution of size of files (measured in lines of code).

Intro
Learn more...
File Size Overall
19% | 12% | 29% | 25% | 13%
Legend:
1001+
501-1000
201-500
101-200
1-100


explore: grouped by folders | grouped by size | sunburst | 3D view
File Size per Extension
1001+
501-1000
201-500
101-200
1-100
py25% | 15% | 39% | 13% | 6%
yaml0% | 0% | 0% | 65% | 34%
cfg0% | 0% | 0% | 0% | 100%
toml0% | 0% | 0% | 0% | 100%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
muse23% | 28% | 35% | 10% | 1%
training52% | 0% | 45% | 0% | 1%
benchmark0% | 0% | 62% | 16% | 20%
scripts0% | 0% | 30% | 43% | 25%
configs0% | 0% | 0% | 65% | 34%
ROOT0% | 0% | 0% | 0% | 100%
Longest Files (Top 50)
File# lines# units
1173 51
train_muse.py
in training
1055 21
740 44
672 38
data.py
in training
499 25
460 34
muse_perf.py
in benchmark
433 10
427 12
417 30
409 7
pre_encode.py
in scripts
350 9
263 25
233 19
m4_shards.yaml
in configs
198 -
193 8
170 3
logging.py
in muse
153 33
149 15
137 11
135 5
127 -
121 -
120 -
119 -
model_quality.py
in benchmark
115 -
113 -
112 -
105 -
103 10
103 -
103 -
103 -
102 -
cc12m_uvit.yaml
in configs
102 -
102 -
102 -
101 -
cc12m_movq.yaml
in configs
100 -
100 -
100 -
100 -
99 -
cc12m.yaml
in configs
98 -
95 -
84 -
imagenet.yaml
in configs
84 -
muse_chart.py
in benchmark
83 2
80 2
78 -
65 2
Files With Most Units (Top 30)
File# lines# units
1173 51
740 44
672 38
460 34
logging.py
in muse
153 33
417 30
263 25
data.py
in training
499 25
train_muse.py
in training
1055 21
233 19
149 15
427 12
137 11
muse_perf.py
in benchmark
433 10
52 10
103 10
pre_encode.py
in scripts
350 9
193 8
409 7
135 5
170 3
muse_chart.py
in benchmark
83 2
muse_table.py
in benchmark
62 2
optimizer.py
in training
34 2
44 2
80 2
65 2
25 1
42 1
41 1
Files With Long Lines (Top 15)

There are 15 files with lines longer than 120 characters. In total, there are 241 long lines.

File# lines# units# long lines
m4_shards.yaml
in configs
198 - 198
19 - 19
muse_chart.py
in benchmark
83 2 6
muse_perf.py
in benchmark
433 10 2
train_muse.py
in training
1055 21 2
103 - 2
105 - 2
100 - 2
112 - 2
740 44 1
409 7 1
1173 51 1
427 12 1
135 5 1
119 - 1