GoogleCloudPlatform / ml-auto-solutions

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 272 units with 3,214 lines of code in units (19.9% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
3 medium complex units (118 lines of code)
13 simple units (468 lines of code)
256 very simple units (2,628 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 stream_logs() in xlml/utils/gke.py	63	21	1
def compare_folders() in dags/map_reproducibility/utils/file_comparison.py	36	19	2
def cleanup_cmds() in dags/map_reproducibility/utils/common_utils.py	19	12	0
def get_concatenated_list_of_params() in dags/inference/maxtext_inference_microbenchmark.py	58	10	1
def delete_queued_resource() in xlml/utils/tpu.py	63	10	1
def get_version_mapping() in dags/pytorch_xla/configs/pytorchxla_torchbench_config.py	20	9	1
def extract_and_write_to_jsonl_pattern() in dags/inference/utils/maxtext_gpu_microbenchmark_jsonl_converter.py	33	8	2
def insert() in xlml/utils/bigquery.py	28	8	2
def execute_workload_commands() in dags/map_reproducibility/utils/sample_workload_utils.py	26	7	2
def run() in xlml/apis/task.py	31	7	1
def show_diff() in dags/map_reproducibility/utils/file_comparison.py	25	6	2
def find_xprof_gcs_path() in dags/map_reproducibility/utils/common_utils.py	21	6	1
def get_scheduled_time() in dags/map_reproducibility/utils/common_utils.py	52	6	3
def wait_for_resource_creation() in xlml/utils/gpu.py	32	6	1
def delete_resource() in xlml/utils/gpu.py	48	6	3
def clean_up_idle_nodes() in xlml/utils/tpu.py	31	6	2
def convert_to_jsonl() in dags/inference/utils/trtllm_bench_jsonl_converter.py	18	5	2
def get_internal_docker_image() in dags/map_reproducibility/utils/common_utils.py	16	5	2
def extract_data() in dags/inference/utils/trtllm_bench_jsonl_converter.py	9	4	2
def model_install_cmds() in dags/pytorch_xla/configs/pytorchxla_torchbench_config.py	12	4	1
def model_install_cmds() in dags/pytorch_xla/configs/pytorchxla_torchbench_config.py	12	4	1
def get_nvidia_driver_install_cmd() in dags/pytorch_xla/configs/pytorchxla_torchbench_config.py	9	4	1
def sample_workload_gcs_to_cns_cmds() in dags/map_reproducibility/utils/sample_workload_utils.py	13	4	2
def get_accelerator_type() in dags/map_reproducibility/utils/common_utils.py	7	4	1
def get_cluster() in dags/map_reproducibility/utils/common_utils.py	7	4	1
def get_image_version() in dags/map_reproducibility/utils/common_utils.py	10	4	2
def is_valid_metric() in xlml/utils/bigquery.py	5	4	2
def get_ip_address() in xlml/utils/gpu.py	11	4	1
def torchvision() in dags/pytorch_xla/nightly.py	68	3	0
def torchvision() in dags/pytorch_xla/r2_7.py	66	3	0
def simple_timeit() in dags/multipod/legacy_tests/gpt1-like.py	12	3	3
def update_run_name_from_quantization_config() in dags/multipod/configs/maxtext_sweep_gke_config.py	7	3	2
def git_cookie_authdaemon() in dags/map_reproducibility/utils/common_utils.py	13	3	0
def get_skip_steps_for_metrics_calculation() in dags/map_reproducibility/utils/common_utils.py	6	3	1
def parse_internal_config_filename() in dags/map_reproducibility/utils/common_utils.py	25	3	2
def parse_internal_config_content() in dags/map_reproducibility/utils/common_utils.py	14	3	2
def get_software_id() in dags/map_reproducibility/utils/common_utils.py	7	3	1
def main() in dags/map_reproducibility/internal_runs/sample_a3ultra_maxtext_single_run.py	17	3	0
def main() in dags/map_reproducibility/internal_runs/sample_a4_maxtext_single_run.py	15	3	0
def create_adaptive_backfill_dag() in dags/map_reproducibility/internal_runs/backfill_dags.py	11	3	0
def main() in dags/map_reproducibility/internal_runs/sample_a3mega_maxtext_single_run.py	17	3	0
def get_vllm_tpu_setup_cmds() in dags/solutions_team/configs/vllm/vllm_benchmark_config.py	13	3	0
def get_gcs_file_location_with_regex() in xlml/utils/metric.py	18	3	1
def is_valid_gpu_version() in xlml/utils/xpk.py	4	3	1
def wait_all_pods_ready() in xlml/utils/gke.py	16	3	1
def wait_for_ready_queued_resource() in xlml/utils/tpu.py	17	3	1
def run_with_existing_instance() in xlml/apis/task.py	24	3	1
def gen_layers() in dags/multipod/legacy_tests/gpt1-like.py	6	2	1
def multiply_layers() in dags/multipod/legacy_tests/gpt1-like.py	5	2	2
def run_maxtext_tests() in dags/multipod/maxtext_gpu_end_to_end.py	94	2	1