huggingface / optimum-habana 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 1,769 units with 19,367 lines of code in units (32.8% of code).

3 very complex units (1,041 lines of code)
4 complex units (347 lines of code)
51 medium complex units (2,147 lines of code)
78 simple units (1,994 lines of code)
1,633 very simple units (13,838 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 __post_init__() in optimum/habana/transformers/training_args.py	414	132	1
def _prepare_deepspeed() in optimum/habana/accelerate/accelerator.py	224	55	2
def adapt_transformers_to_gaudi() in optimum/habana/transformers/modeling_utils.py	403	54	0
def _setup_devices() in optimum/habana/transformers/training_args.py	103	41	1
def gaudi_prepare_inputs_for_generation() in optimum/habana/peft/peft_model.py	58	27	4
def _convert_model() in optimum/habana/accelerate/utils/transformer_engine.py	79	27	3
def prepare_model() in optimum/habana/accelerate/accelerator.py	107	26	4
def _load_best_model() in optimum/habana/transformers/trainer.py	84	25	1
def finalize_beams() in optimum/habana/transformers/generation/utils.py	73	21	4
def _pad_past_key_values() in optimum/habana/transformers/generation/utils.py	22	20	2
def _push_from_checkpoint() in optimum/habana/transformers/trainer.py	53	20	2
def _attn() in optimum/habana/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py	49	19	6
def handle_single_conversation() in optimum/habana/transformers/models/glm4v/tokenization_chatglm.py	65	19	1
def step() in optimum/habana/trl/trainer/ddpo_trainer.py	69	19	3
def st_gaudi_data_collator_call() in optimum/habana/sentence_transformers/st_gaudi_data_collator.py	40	17	3
def create_optimizer() in optimum/habana/transformers/trainer.py	44	17	1
def _load_optimizer_and_scheduler() in optimum/habana/transformers/trainer.py	45	16	2
def prepare_inputs_for_generation() in optimum/habana/transformers/models/gpt_neo/modeling_gpt_neo.py	40	15	5
def gaudi_DetrLoss_forward() in optimum/habana/transformers/models/detr/modeling_detr.py	28	15	3
def _save_optimizer_and_scheduler() in optimum/habana/transformers/trainer.py	35	15	2
def _save() in optimum/habana/transformers/trainer.py	37	15	3
def backward() in optimum/habana/transformers/gradient_checkpointing.py	42	15	2
def prepare_latents() in optimum/habana/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py	49	15	8
def build_chat_input() in optimum/habana/transformers/models/baichuan/generation_utils.py	40	14	4
def forward() in optimum/habana/transformers/models/deepseek_v3/modeling_deepseek_v3.py	66	14	2
def _prepare_input() in optimum/habana/transformers/trainer.py	23	14	3
def save_model() in optimum/habana/transformers/trainer.py	32	14	3
def load_generation_config() in optimum/habana/transformers/trainer_seq2seq.py	25	14	2
def gaudi_validate_environment() in optimum/habana/quantizers/bitsandbytes.py	36	14	3
def from_pretrained() in optimum/habana/diffusers/pipelines/pipeline_utils.py	29	14	4
def tiled_decode_gaudi() in optimum/habana/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py	51	14	3
def compute_query_states() in optimum/habana/peft/layer.py	37	13	2
def get_repo_root() in optimum/habana/checkpoint_utils.py	35	13	3
def _merge_input_ids_with_image_features() in optimum/habana/transformers/models/llava_next/modeling_llava_next.py	48	13	6
def _merge_input_ids_with_image_features() in optimum/habana/transformers/models/llava_onevision/modeling_llava_onevision.py	48	13	6
def _upcast_and_reordered_attn() in optimum/habana/transformers/models/gpt2/modeling_gpt2.py	32	13	6
def _wrap_model() in optimum/habana/transformers/trainer.py	29	13	4
def get_batch_samples_transformers() in optimum/habana/transformers/trainer.py	26	13	4
def gaudi_awq_config_post_init() in optimum/habana/transformers/integrations/awq.py	41	13	1
def _split_inputs_into_batches() in optimum/habana/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py	41	13	7
def _split_inputs_into_batches() in optimum/habana/diffusers/pipelines/flux/pipeline_flux_img2img.py	40	13	6
def _split_inputs_into_batches() in optimum/habana/diffusers/pipelines/flux/pipeline_flux.py	40	13	6
def gaudi_qwen2moe_block_sparse_moe_forward() in optimum/habana/transformers/models/qwen2_moe/modeling_qwen2_moe.py	55	12	2
def _get_input_update_settings() in optimum/habana/transformers/trainer.py	29	12	2
def _get_train_sampler() in optimum/habana/transformers/trainer.py	32	12	1
def create_accelerator_and_postprocess() in optimum/habana/transformers/trainer.py	78	12	1
def _train_batched_samples() in optimum/habana/trl/trainer/ddpo_trainer.py	60	12	5
def gaudi_bitsandbytesconfig_post_init() in optimum/habana/quantizers/bitsandbytes.py	20	12	1
def prepare_latents() in optimum/habana/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py	46	12	8
def _wrap_model() in optimum/habana/sentence_transformers/st_gaudi_trainer.py	27	11	4