amazon-research / gluonmm
Conditional Complexity

The distribution of complexity of units (measured with McCabe index).

Intro
  • Conditional complexity (also called cyclomatic complexity) is a term used to measure the complexity of software. The term refers to the number of possible paths through a program function. A higher value ofter means higher maintenance and testing costs (infosecinstitute.com).
  • Conditional complexity is calculated by counting all conditions in the program that can affect the execution path (e.g. if statement, loops, switches, and/or operators, try and catch blocks...).
  • Conditional complexity is measured at the unit level (methods, functions...).
  • Units are classified in four categories based on the measured McCabe index: 1-5 (simple units), 6-10 (medium complex units), 11-25 (complex units), 26+ (very complex units).
Learn more...
Conditional Complexity Overall
  • There are 219 units with 3,341 lines of code in units (51.3% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 9 medium complex units (420 lines of code)
    • 18 simple units (557 lines of code)
    • 192 very simple units (2,364 lines of code)
0% | 0% | 12% | 16% | 70%
Legend:
51+
26-50
11-25
6-10
1-5
Alternative Visuals
Conditional Complexity per Extension
51+
26-50
11-25
6-10
1-5
py0% | 0% | 12% | 16% | 70%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
src/transformers/utils0% | 0% | 21% | 34% | 43%
src/transformers/data0% | 0% | 19% | 36% | 43%
src/transformers/models0% | 0% | 3% | 6% | 90%
scripts/image_classification0% | 0% | 78% | 21% | 0%
scripts/action_recognition0% | 0% | 71% | 28% | 0%
src/transformers/pipelines0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def main_worker()
in scripts/image_classification/train.py
 67 25 1
def __init__()
in src/transformers/models/vit/vision_transformer.py
 47 17 20
def resize_clip()
in src/transformers/data/datasets/transforms/functional.py
 37 17 3
def download()
in src/transformers/utils/model_utils.py
 35 15 4
def main_worker()
in scripts/action_recognition/train.py
 47 15 1
def deploy_model()
in src/transformers/utils/model_utils.py
 32 14 3
def _init_vit_weights()
in src/transformers/models/vit/vision_transformer.py
 27 12 4
def build_transform()
in src/transformers/data/datasets/img_cls_datasets.py
 62 12 2
def train_classification()
in src/transformers/utils/image_classification.py
 66 11 10
def load_model()
in src/transformers/utils/model_utils.py
 24 10 3
def train_classification()
in src/transformers/utils/video_action_recognition.py
 77 10 10
def __call__()
in src/transformers/data/datasets/transforms/volume_transforms.py
 32 10 2
def inflate_model()
in src/transformers/models/vidtr/vidtr_split.py
 23 9 4
def __getitem__()
in src/transformers/data/datasets/kinetics_datasets.py
 25 9 2
def loadvideo_test_decord()
in src/transformers/data/datasets/kinetics_datasets.py
 31 9 2
def validate_classification()
in src/transformers/utils/image_classification.py
 52 8 5
def __init__()
in src/transformers/models/swin/swin_transformer.py
 43 8 14
def build_dataloader()
in src/transformers/data/datasets/kinetics_datasets.py
 33 8 1
def main_worker()
in scripts/action_recognition/test.py
 19 8 1
def set_weight_decay()
in src/transformers/utils/optimizer.py
 13 7 2