facebookresearch / AttentiveNAS
File Size

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

Intro
  • File size measurements show the distribution of size of files.
  • Files are classified in four categories based on their size (lines of code): 1-100 (very small files), 101-200 (small files), 201-500 (medium size files), 501-1000 (long files), 1001+(very long files).
  • It is a good practice to keep files small. Long files may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.
Learn more...
File Size Overall
  • There are 31 files with 3,158 lines of code.
    • 0 very long files (0 lines of code)
    • 0 long files (0 lines of code)
    • 5 medium size files (1,437 lines of codeclsfd_ftr_w_mp_ins)
    • 5 small files (661 lines of code)
    • 21 very small files (1,060 lines of code)
0% | 0% | 45% | 20% | 33%
Legend:
1001+
501-1000
201-500
101-200
1-100


explore: zoomable circles | sunburst | 3D view
File Size per Extension
1001+
501-1000
201-500
101-200
1-100
py0% | 0% | 49% | 14% | 36%
yml0% | 0% | 0% | 100% | 0%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
models/modules0% | 0% | 57% | 32% | 10%
models0% | 0% | 77% | 0% | 22%
data0% | 0% | 65% | 0% | 34%
ROOT0% | 0% | 100% | 0% | 0%
configs0% | 0% | 0% | 100% | 0%
solver0% | 0% | 0% | 56% | 43%
utils0% | 0% | 0% | 0% | 100%
evaluate0% | 0% | 0% | 0% | 100%
sampler0% | 0% | 0% | 0% | 100%
Longest Files (Top 31)
File# lines# units
attentive_nas_dynamic_model.py
in models
 361 21
static_layers.py
in models/modules
 282 33
auto_augment_tf.py
in data
 275 38
train_attentive_nas.py
in root
 268 5
dynamic_layers.py
in models/modules
 251 25
dynamic_ops.py
in models/modules
 184 13
eval_attentive_nas_models.yml
in configs
 134 -
nn_base.py
in models/modules
 116 15
train_attentive_nas_models.yml
in configs
 116 -
lr_scheduler.py
in solver
 111 13
data_transform.py
in data
 89 4
attentive_nas_sampler.py
in sampler
 86 8
config.py
in utils
 83 8
build.py
in solver
 83 2
attentive_nas_eval.py
in evaluate
 82 1
flops_counter.py
in utils
 72 4
attentive_nas_static_model.py
in models
 69 7
nn_utils.py
in models/modules
 69 8
imagenet_eval.py
in evaluate
 66 2
saver.py
in utils
 58 5
data_loader.py
in data
 54 2
comm.py
in utils
 50 7
progress.py
in utils
 49 8
loss_ops.py
in utils
 45 4
logging.py
in utils
 37 3
model_factory.py
in models
 35 1
activations.py
in models/modules
 29 7
__init__.py
in models
 1 -
__init__.py
in models/modules
 1 -
__init__.py
in solver
 1 -
__init__.py
in data
 1 -
Files With Most Units (Top 20)
File# lines# units
auto_augment_tf.py
in data
 275 38
static_layers.py
in models/modules
 282 33
dynamic_layers.py
in models/modules
 251 25
attentive_nas_dynamic_model.py
in models
 361 21
nn_base.py
in models/modules
 116 15
dynamic_ops.py
in models/modules
 184 13
lr_scheduler.py
in solver
 111 13
config.py
in utils
 83 8
progress.py
in utils
 49 8
nn_utils.py
in models/modules
 69 8
attentive_nas_sampler.py
in sampler
 86 8
comm.py
in utils
 50 7
attentive_nas_static_model.py
in models
 69 7
activations.py
in models/modules
 29 7
train_attentive_nas.py
in root
 268 5
saver.py
in utils
 58 5
loss_ops.py
in utils
 45 4
flops_counter.py
in utils
 72 4
data_transform.py
in data
 89 4
logging.py
in utils
 37 3
Files With Long Lines (Top 6)

There are 6 files with lines longer than 120 characters. In total, there are 10 long lines.

File# lines# units# long lines
attentive_nas_dynamic_model.py
in models
 361 21 3
dynamic_layers.py
in models/modules
 251 25 3
attentive_nas_static_model.py
in models
 69 7 1
static_layers.py
in models/modules
 282 33 1
lr_scheduler.py
in solver
 111 13 1
attentive_nas_sampler.py
in sampler
 86 8 1