facebookresearch / graph2nn
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 4,538 files with 231,530 lines of code.
    • 0 very long files (0 lines of code)
    • 0 long files (0 lines of code)
    • 5 medium size files (1,482 lines of codeclsfd_ftr_w_mp_ins)
    • 108 small files (11,352 lines of code)
    • 4,425 very small files (218,696 lines of code)
0% | 0% | <1% | 4% | 94%
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% | 44% | 28% | 26%
yaml0% | 0% | 0% | 4% | 95%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
pycls/models0% | 0% | 64% | 22% | 13%
tools0% | 0% | 100% | 0% | 0%
ROOT0% | 0% | 97% | 0% | 2%
configs/baselines/imagenet/efficient_imagenet0% | 0% | 0% | 100% | 0%
pycls/utils0% | 0% | 0% | 47% | 52%
pycls/datasets0% | 0% | 0% | 33% | 66%
pycls0% | 0% | 0% | 99% | <1%
configs/baselines/cifar10/mlp_cifar100% | 0% | 0% | 0% | 100%
configs/baselines/imagenet/resnet34_imagenet0% | 0% | 0% | 0% | 100%
configs/baselines/imagenet/resnet50_imagenet0% | 0% | 0% | 0% | 100%
configs/baselines/imagenet/resnet34sep_imagenet0% | 0% | 0% | 0% | 100%
configs/baselines/imagenet/cnn_imagenet0% | 0% | 0% | 0% | 100%
configs/baselines/imagenet0% | 0% | 0% | 0% | 100%
configs/baselines/cifar10/mlp_cifar10_bio0% | 0% | 0% | 0% | 100%
configs/baselines/cifar100% | 0% | 0% | 0% | 100%
Longest Files (Top 50)
File# lines# units
resnet.py
in pycls/models
361 36
efficientnet.py
in pycls/models
307 27
train_net.py
in tools
305 9
relation_graph.py
in pycls/models
296 27
yaml_gen.py
in root
213 6
meters.py
in pycls/utils
187 25
mlp.py
in pycls/models
174 27
metrics.py
in pycls/utils
168 13
cnn.py
in pycls/models
160 22
transforms.py
in pycls/datasets
134 10
config.py
in pycls
125 3
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.317479_p0.004474_aggsum_graphseed1_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.28157_p0.980034_aggsum_graphseed2_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.34518_p0.403799_aggsum_graphseed3_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.643117_p0.58147_aggsum_graphseed11_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.446861_p0.020682_aggsum_graphseed18_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.27008_p0.483932_aggsum_graphseed5_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.834545_p0.019731_aggsum_graphseed28_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.26106_p0.300847_aggsum_graphseed11_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.2633_p0.953725_aggsum_graphseed16_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.44103_p0.442959_aggsum_graphseed22_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.806796_p0.541381_aggsum_graphseed12_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.350341_p0.025772_aggsum_graphseed2_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.26106_p0.098836_aggsum_graphseed4_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.252193_p0.665943_aggsum_graphseed0_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.806796_p0.541381_aggsum_graphseed12_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.334973_p0.750338_aggsum_graphseed3_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.834545_p0.019731_aggsum_graphseed28_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbconv_talkmodedense_num16_messagews_sparsity1.0_p0.0_aggsum_graphseed1_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.30527_p0.858257_aggsum_graphseed2_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.274647_p0.025772_aggsum_graphseed5_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.875_p0.315701_aggsum_graphseed16_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.279253_p0.617722_aggsum_graphseed7_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.446861_p0.020682_aggsum_graphseed18_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.384823_p0.066319_aggsum_graphseed26_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.290935_p0.013702_aggsum_graphseed16_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.26106_p0.300847_aggsum_graphseed11_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.25_p0.10095_aggsum_graphseed4_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.756507_p0.023669_aggsum_graphseed22_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.44103_p0.442959_aggsum_graphseed22_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.2633_p0.953725_aggsum_graphseed16_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.404059_p0.779589_aggsum_graphseed18_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.317479_p0.004474_aggsum_graphseed1_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.258829_p0.517052_aggsum_graphseed23_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.643117_p0.58147_aggsum_graphseed11_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.27008_p0.483932_aggsum_graphseed5_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs512_8gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.28157_p0.980034_aggsum_graphseed2_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.529334_p0.576381_aggsum_graphseed16_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.34518_p0.403799_aggsum_graphseed3_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
EN-B0_bs64_1gpu_nms_transmbtalkconv_talkmodedense_num16_messagews_sparsity0.30527_p0.858257_aggsum_graphseed2_starttrainseed1_endtrainseed2_keepTrue_add1x10_upperTrue_matchTrue_epoch100.yaml
in configs/baselines/imagenet/efficient_imagenet/all
102 -
Files With Most Units (Top 20)
File# lines# units
resnet.py
in pycls/models
361 36
mlp.py
in pycls/models
174 27
efficientnet.py
in pycls/models
307 27
relation_graph.py
in pycls/models
296 27
meters.py
in pycls/utils
187 25
cnn.py
in pycls/models
160 22
metrics.py
in pycls/utils
168 13
transforms.py
in pycls/datasets
134 10
train_net.py
in tools
305 9
load_graph.py
in pycls/datasets
90 7
logging.py
in pycls/utils
70 7
checkpoint.py
in pycls/utils
46 7
yaml_gen.py
in root
213 6
cifar10.py
in pycls/datasets
51 6
imagenet.py
in pycls/datasets
65 5
lr_policy.py
in pycls/utils
22 5
net.py
in pycls/utils
72 5
error_handler.py
in pycls/utils
23 5
loader.py
in pycls/datasets
47 4
timer.py
in pycls/utils
17 4
Files With Long Lines (Top 1)

There is only one file with lines longer than 120 characters. In total, there is only one long line.

File# lines# units# long lines
metrics.py
in pycls/utils
168 13 1