amazon-research / fact-check-summarization
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 289 files with 33,591 lines of code.
    • 1 very long files (1,130 lines of code)
    • 6 long files (3,792 lines of code)
    • 40 medium size files (11,886 lines of codeclsfd_ftr_w_mp_ins)
    • 70 small files (9,965 lines of code)
    • 172 very small files (6,818 lines of code)
3% | 11% | 35% | 29% | 20%
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
py3% | 11% | 35% | 28% | 20%
cu0% | 0% | 64% | 35% | 0%
cpp0% | 0% | 0% | 64% | 35%
pyx0% | 0% | 0% | 74% | 25%
cuh0% | 0% | 0% | 0% | 100%
lua0% | 0% | 0% | 0% | 100%
h0% | 0% | 0% | 0% | 100%
toml0% | 0% | 0% | 0% | 100%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
preprocess36% | 42% | 0% | 17% | 3%
fairseq/models0% | 24% | 48% | 18% | 8%
fairseq0% | 13% | 54% | 22% | 9%
fairseq/tasks0% | 0% | 52% | 42% | 4%
fairseq/data0% | 0% | 36% | 25% | 37%
fairseq/modules0% | 0% | 33% | 31% | 35%
fairseq_cli0% | 0% | 47% | 40% | 11%
fairseq/optim0% | 0% | 18% | 35% | 45%
fairseq/clib0% | 0% | 43% | 45% | 11%
fairseq/logging0% | 0% | 45% | 54% | <1%
scripts0% | 0% | 0% | 70% | 29%
fairseq/criterions0% | 0% | 0% | 44% | 55%
ROOT0% | 0% | 0% | 53% | 46%
fairseq/benchmark0% | 0% | 0% | 0% | 100%
Longest Files (Top 50)
File# lines# units
sm_inference_asum.py
in preprocess
 1130 16
evaluate_hypo.py
in preprocess
 792 13
transformer.py
in fairseq/models
 744 39
wav2vec.py
in fairseq/models
 629 25
lightconv.py
in fairseq/models
 554 29
trainer.py
in fairseq
 543 29
data_prepro_clean.py
in preprocess
 530 16
sequence_generator.py
in fairseq
 499 22
options.py
in fairseq
 482 21
lstm.py
in fairseq/models
 459 23
fconv.py
in fairseq/models
 455 31
fconv_self_att.py
in fairseq/models
 448 26
indexed_dataset.py
in fairseq/data
 398 62
levenshtein_transformer.py
in fairseq/models/nat
 381 15
multihead_attention.py
in fairseq/modules
 370 10
preprocess.py
in fairseq_cli
 368 8
checkpoint_utils.py
in fairseq
 360 13
utils.py
in fairseq
 354 38
translation.py
in fairseq/tasks
 331 14
nonautoregressive_transformer.py
in fairseq/models/nat
 324 19
semisupervised_translation.py
in fairseq/tasks
 316 11
fp16_optimizer.py
in fairseq/optim
 298 37
lightconv_cuda_kernel.cu
in fairseq/modules/lightconv_layer
 285 -
edit_dist.cu
in fairseq/clib/libnat_cuda
 284 -
dictionary.py
in fairseq/data
 282 29
denoising_dataset.py
in fairseq/data
 281 18
fairseq_model.py
in fairseq/models
 265 45
model.py
in fairseq/models/roberta
 265 22
multilingual_masked_lm.py
in fairseq/tasks
 257 10
progress_bar.py
in fairseq/logging
 257 38
multilingual_translation.py
in fairseq/tasks
 256 19
masked_lm.py
in fairseq/models
 250 13
train.py
in fairseq_cli
 244 8
transformer_layer.py
in fairseq/modules
 243 9
transformer_lm.py
in fairseq/models
 237 12
iterative_refinement_generator.py
in fairseq
 235 4
translation_with_unlikelihood.py
in fairseq/tasks
 234 12
fairseq_task.py
in fairseq/tasks
 232 21
language_pair_dataset.py
in fairseq/data
 229 13
model.py
in fairseq/models/bart
 226 12
iterators.py
in fairseq/data
 225 37
insertion_transformer.py
in fairseq/models/nat
 215 16
levenshtein_utils.py
in fairseq/models/nat
 211 9
file_utils.py
in fairseq
 210 12
block_pair_dataset.py
in fairseq/data/legacy
 210 13
lightweight_convolution.py
in fairseq/modules
 209 14
dynamic_convolution.py
in fairseq/modules
 201 12
meters.py
in fairseq/logging
 199 40
hub_utils.py
in fairseq
 197 23
downsampled_multihead_attention.py
in fairseq/modules
 197 8
Files With Most Units (Top 20)
File# lines# units
indexed_dataset.py
in fairseq/data
 398 62
fairseq_model.py
in fairseq/models
 265 45
meters.py
in fairseq/logging
 199 40
transformer.py
in fairseq/models
 744 39
utils.py
in fairseq
 354 38
progress_bar.py
in fairseq/logging
 257 38
fp16_optimizer.py
in fairseq/optim
 298 37
iterators.py
in fairseq/data
 225 37
fconv.py
in fairseq/models
 455 31
trainer.py
in fairseq
 543 29
lightconv.py
in fairseq/models
 554 29
dictionary.py
in fairseq/data
 282 29
fconv_self_att.py
in fairseq/models
 448 26
wav2vec.py
in fairseq/models
 629 25
hub_utils.py
in fairseq
 197 23
bmuf.py
in fairseq/optim
 145 23
lstm.py
in fairseq/models
 459 23
sequence_generator.py
in fairseq
 499 22
model.py
in fairseq/models/roberta
 265 22
options.py
in fairseq
 482 21
Files With Long Lines (Top 20)

There are 25 files with lines longer than 120 characters. In total, there are 79 long lines.

File# lines# units# long lines
lightconv.py
in fairseq/models
 554 29 14
transformer.py
in fairseq/models
 744 39 12
data_prepro_clean.py
in preprocess
 530 16 9
transformer_lm.py
in fairseq/models
 237 12 5
average_checkpoints.py
in scripts
 105 3 5
evaluate_hypo.py
in preprocess
 792 13 4
fconv.py
in fairseq/models
 455 31 3
label_smoothed_cross_entropy_with_multitask.py
in fairseq/criterions
 193 8 3
preprocess.py
in fairseq_cli
 368 8 3
model.py
in fairseq/models/bart
 226 12 2
model.py
in fairseq/models/roberta
 265 22 2
pyx
token_block_utils_fast.pyx
in fairseq/data
 153 1 2
round_robin_zip_datasets.py
in fairseq/data
 69 10 2
sm_inference_asum.py
in preprocess
 1130 16 2
semisupervised_translation.py
in fairseq/tasks
 316 11 1
lightconv_cuda_kernel.cu
in fairseq/modules/lightconv_layer
 285 - 1
cuda_utils.cu
in fairseq/modules
 169 - 1
dynamic_convolution.py
in fairseq/modules
 201 12 1
wav2vec.py
in fairseq/models
 629 25 1
hub_interface.py
in fairseq/models/bart
 164 10 1