• 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.

• There are 217 files with 17,317 lines of code.
• 0 very long files (0 lines of code)
• 2 long files (1,051 lines of code)
• 18 medium size files (5,423 lines of codeclsfd_ftr_w_mp_ins)
• 34 small files (4,696 lines of code)
• 163 very small files (6,147 lines of code)

There are 48 files with lines longer than 120 characters. In total, there are 199 long lines.

File	# lines	# units	# long lines
main.py in Classification	366	-	34
SyncND.py in Classification/models	288	17	15
simple.py in Classification/models	123	6	12
rfnorm.py in Classification/models	477	14	12
deconv.py in MaskRCNN/pytorch/maskrcnn_benchmark/layers	362	15	9
deconv.py in Classification/models	362	15	9
SyncND.py in Segmentation/models/segmentation	141	7	7
resnext.py in Classification/models	104	10	7
main_imagenet.py in Classification	534	15	6
densenet.py in Classification/models	110	13	6
resnet.py in MaskRCNN/pytorch/maskrcnn_benchmark/modeling/backbone	469	20	5
deconv.py in Segmentation/models/segmentation	256	12	5
arg_parser.py in Classification	61	1	5
resnet_imagenet.py in Classification/models	230	20	5
resnet.py in Classification/models	150	13	5
roi_box_predictors.py in MaskRCNN/pytorch/maskrcnn_benchmark/modeling/roi_heads/box_head	71	5	4
ROIAlign_cuda.cu in MaskRCNN/pytorch/maskrcnn_benchmark/csrc/cuda	287	-	4
gen_cmd.py in Classification	22	-	4
dpn.py in Classification/models	108	8	4
rpn.py in MaskRCNN/pytorch/maskrcnn_benchmark/modeling/rpn	96	7	3