GoogleCloudPlatform / accelerated-platforms

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 82 units with 1,230 lines of code in units (4.3% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
2 medium complex units (66 lines of code)
13 simple units (356 lines of code)
67 very simple units (808 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 generate_multimodal_embeddings() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	42	12	0
def extract_product_details() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	24	11	1
def generate_content() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	62	10	1
def extract_product_names() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	18	10	2
def generate_image_embeddings() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	36	10	0
def process_input() in use-cases/rag-pipeline/frontend/src/interface.py	16	10	2
def parse_attributes() in modules/python/src/datapreprocessing/datacleaner.py	19	9	2
def configure_cloud_trace() in use-cases/rag-pipeline/backend/src/backend_service.py	28	7	1
def get_image_embeddings() in use-cases/rag-pipeline/backend/src/generate_embeddings.py	26	7	1
def prep_product_desc() in modules/python/src/datapreprocessing/datacleaner.py	20	6	2
def run_remote() in modules/python/src/datapreprocessing/ray_utils.py	31	6	1
def generate_qa() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	26	6	2
def generate_text_embeddings() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	23	6	0
def get_multimodal_embeddings() in use-cases/rag-pipeline/backend/src/generate_embeddings.py	26	6	2
def get_text_embeddings() in use-cases/rag-pipeline/backend/src/generate_embeddings.py	25	6	1
def prep_cat() in modules/python/src/datapreprocessing/datacleaner.py	13	5	2
def data_prep() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	17	5	1
def download_image_from_gcs() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	15	5	1
def query_instruction_tuned_gemma() in use-cases/rag-pipeline/backend/src/rerank.py	29	5	1
def get_embeddings() in use-cases/rag-pipeline/backend/src/generate_embeddings.py	15	5	2
def populate_table() in use-cases/rag-pipeline/alloy-db-setup/src/db_setup.py	27	5	0
def __getattr__() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/openai_credentials_refresher.py	19	4	2
def predict() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	30	4	1
def predict() in use-cases/inferencing/batch-inference/src/run_batch_predictions.py	40	4	1
def process_rag_input() in modules/python/src/datapreprocessing/datacleaner.py	39	3	2
def evaluate() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	5	3	1
def prompt_generation() in use-cases/rag-pipeline/backend/src/prompt_helper.py	6	3	2
def batchType() in use-cases/inferencing/batch-inference/src/run_batch_predictions.py	3	3	1
def reformat() in modules/python/src/datapreprocessing/datacleaner.py	4	2	2
def split_dataframe() in modules/python/src/datapreprocessing/dataprep.py	7	2	1
def filter_low_value_count_rows() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	5	2	3
def prep_context() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	47	2	0
def graceful_shutdown() in use-cases/model-fine-tuning-pipeline/data-preparation/gemma-it/src/dataprep.py	4	2	2
def graceful_shutdown() in use-cases/model-fine-tuning-pipeline/data-processing/ray/src/preprocessing_finetuning.py	4	2	2
def graceful_shutdown() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	4	2	2
def count_no_products_prediction() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	3	2	2
def calculate_accuracy() in use-cases/model-fine-tuning-pipeline/model-eval/src/validate_fine_tuned_model.py	25	2	1
def graceful_shutdown() in use-cases/model-fine-tuning-pipeline/fine-tuning/pytorch/src/fine_tune.py	4	2	2
def formatting_prompts_func() in use-cases/model-fine-tuning-pipeline/fine-tuning/pytorch/src/fine_tune.py	6	2	1
def get_current_node_id_and_rank() in use-cases/model-fine-tuning-pipeline/fine-tuning/pytorch/src/fine_tune.py	19	2	0
def get_text_embedding() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	8	2	1
def get_image_embedding() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	8	2	1
def get_multimodal_embedding() in use-cases/rag-pipeline/embedding-models/multimodal-embedding/src/blip2_server.py	9	2	2
def graceful_shutdown() in use-cases/rag-pipeline/data-preprocessing/src/preprocessing_rag.py	4	2	2
def initialize_database() in use-cases/rag-pipeline/alloy-db-setup/src/db_setup.py	24	2	0
def graceful_shutdown() in use-cases/inferencing/batch-inference/src/run_batch_predictions.py	4	2	2
def graceful_shutdown() in use-cases/inferencing/benchmark/src/tasks.py	4	2	2
def __init__() in modules/python/src/datapreprocessing/datacleaner.py	2	1	1
def extract_url() in modules/python/src/datapreprocessing/datacleaner.py	2	1	2
def download_image() in modules/python/src/datapreprocessing/datacleaner.py	7	1	0