huggingface / api-inference-community Conditional Complexity

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 325 units with 2,846 lines of code in units (45.5% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
11 medium complex units (595 lines of code)
13 simple units (319 lines of code)
301 very simple units (1,932 lines of code)

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

3D view of all units

Conditional Complexity per Extension

51+

26-50

11-25

6-10

1-5

Conditional Complexity per Logical Component

primary logical decomposition

51+

26-50

11-25

6-10

1-5

Most Complex Units

Top 50 most complex units

Unit	# lines	McCabe index	# params
def __init__() in docker_images/diffusers/app/pipelines/image_to_image.py	102	21	2
def __call__() in docker_images/sklearn/app/pipelines/common.py	45	19	2
def _load_textual_embeddings() in docker_images/diffusers/app/lora.py	47	15	3
def call_pipe() in api_inference_community/routes.py	79	14	5
def __init__() in docker_images/diffusers/app/pipelines/text_to_image.py	57	13	2
def __call__() in docker_images/diffusers/app/pipelines/text_to_image.py	30	13	3
def _process_req() in docker_images/diffusers/app/pipelines/image_to_image.py	71	13	4
def _load_lora_adapter() in docker_images/diffusers/app/lora.py	54	13	2
def already_left() in api_inference_community/routes.py	42	13	1
def __init__() in docker_images/sklearn/app/pipelines/common.py	29	12	2
def _process_req() in docker_images/latent-to-image/app/pipelines/latent_to_image.py	39	11	3
def cached_revision_path() in api_inference_community/hub.py	25	10	3
def main() in build_docker.py	48	9	0
def __init__() in docker_images/fairseq/app/pipelines/audio_to_audio.py	71	8	2
def __init__() in docker_images/latent-to-image/app/pipelines/latent_to_image.py	24	8	2
def model_from_hfconfig() in docker_images/k2/app/common.py	31	7	2
def resolve_dataset() in manage.py	26	7	2
def show() in manage.py	22	7	1
def normalize_payload_audio() in api_inference_community/validation.py	10	7	2
def __init__() in docker_images/timm/app/pipelines/image_classification.py	21	6	2
def decode_waves() in docker_images/k2/app/common.py	10	6	2
def _get_lora_weight_name() in docker_images/diffusers/app/lora.py	15	6	1
def traverse_global_assignments() in scripts/export_tasks.py	8	6	3
def get_input_characters() in api_inference_community/routes.py	8	6	1
def __init__() in docker_images/speechbrain/app/pipelines/automatic_speech_recognition.py	14	5	2
def __call__() in docker_images/flair/app/pipelines/token_classification.py	27	5	2
def __call__() in docker_images/stanza/app/pipelines/token_classification.py	25	5	2
def __call__() in docker_images/fasttext/app/pipelines/text_classification.py	15	5	2
def count_current_conns() in docker_images/latent-to-image/app/healthchecks.py	11	5	1
def _process_req() in docker_images/diffusers/app/pipelines/text_to_image.py	19	5	3
def count_current_conns() in docker_images/diffusers/app/healthchecks.py	11	5	1
def resolve_task_framework() in manage.py	13	5	1
def normalize_payload_nlp() in api_inference_community/validation.py	17	5	2
def __init__() in docker_images/nemo/app/pipelines/automatic_speech_recognition.py	11	4	2
def __call__() in docker_images/nemo/app/pipelines/automatic_speech_recognition.py	10	4	2
def __init__() in docker_images/speechbrain/app/pipelines/audio_to_audio.py	14	4	2
def __init__() in docker_images/speechbrain/app/pipelines/text_to_speech.py	19	4	2
def __call__() in docker_images/speechbrain/app/pipelines/text_to_speech.py	11	4	2
def get_type() in docker_images/speechbrain/app/common.py	11	4	2
def get_vocoder_model_id() in docker_images/speechbrain/app/common.py	11	4	1
def get_hfconfig() in docker_images/k2/app/common.py	12	4	2
def load_model_config_from_hf() in docker_images/mindspore/app/pipelines/image_classification.py	22	4	1
def __call__() in docker_images/adapter_transformers/app/pipelines/token_classification.py	10	4	2
def __call__() in docker_images/fairseq/app/pipelines/audio_to_audio.py	25	4	2
def __call__() in docker_images/setfit/app/pipelines/text_classification.py	10	4	2
def _lora_weights_candidates() in docker_images/diffusers/app/lora.py	10	4	1
def get_pipeline() in docker_images/sklearn/app/main.py	8	4	2
def _extract_tasks() in scripts/export_tasks.py	5	4	3
def resolve() in manage.py	20	4	1
def normalize_payload_image() in api_inference_community/validation.py	12	4	1