pytorch / nestedtensor
Features of Interest
Aspects in the source code identified through RegEx patterns.
Intro
Features of interest are any aspects of a software system that can be identified through patterns in code.
Features of interest provide you with a way to focus your attention on relevant parts of the codebase.
Typical examples include, security, TODOs, logging.
A feature of interest may be present in multiple files. Any source code file may be in zero or multiple features of interest.
Overview
GENERAL
TODOs
3,533 LOC (34%)
18 files
|
found text
|
found text per file
1 GENERAL Concerns
The "general" group contains
2
concerns.
TODOs
Unclassified
general
1.1 TODOs
3,533 LOC (34%)
18 files
|
found text
|
found text per file
The following criteria are used to filter files:
files with any line of content like "
.*(TODO|FIXME)( |:| ).*
".
18
files match defined criteria (
3,533
lines of code,
34.3%
vs. main code):
8
*.cpp files (
1,563
lines of code)
6
*.py files (
832
lines of code)
2
*.cu files (
677
lines of code)
2
*.h files (
461
lines of code)
50
lines match the content pattern.
details...
per component - primary logical decomposition
nestedtensor/csrc
in 7 files, 1,474 LOC (31%)
nestedtensor/csrc/cuda
in 3 files, 766 LOC (32%)
benchmarks
in 1 file 91 LOC (7%)
nestedtensor/csrc/utils
in 2 files, 461 LOC (69%)
nestedtensor/nested
in 3 files, 557 LOC (94%)
nestedtensor/csrc/scripts
in 1 file 113 LOC (100%)
nestedtensor/nn
in 1 file 71 LOC (98%)