openai / phasic-policy-gradient - 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 249 units with 1,715 lines of code in units (72.5% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
4 medium complex units (146 lines of code)
16 simple units (337 lines of code)
229 very simple units (1,232 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 main_pcg_sample_entry() in phasic_policy_gradient/graph.py	48	20	2
def parse_dtype() in phasic_policy_gradient/torch_util.py	26	18	1
def plot_experiment() in phasic_policy_gradient/graph_util.py	52	17	9
def singles_to_multi() in phasic_policy_gradient/roller.py	20	11	1
def read_csv() in phasic_policy_gradient/graph_util.py	15	10	2
def format_model() in phasic_policy_gradient/torch_util.py	26	9	2
def writekvs() in phasic_policy_gradient/logger.py	27	9	2
def read_tb() in phasic_policy_gradient/logger.py	30	9	1
def train_fn() in phasic_policy_gradient/train.py	60	8	23
def dumpkvs() in phasic_policy_gradient/logger.py	20	7	1
def rcm() in phasic_policy_gradient/log_save_helper.py	7	6	4
def log() in phasic_policy_gradient/log_save_helper.py	26	6	1
def save() in phasic_policy_gradient/log_save_helper.py	17	6	1
def _fmt_item() in phasic_policy_gradient/minibatch_optimize.py	13	6	2
def mpi_weighted_mean() in phasic_policy_gradient/logger.py	16	6	2
def writekvs() in phasic_policy_gradient/logger.py	24	6	2
def make_output_format() in phasic_policy_gradient/logger.py	14	6	3
def residual() in phasic_policy_gradient/impala_cnn.py	10	6	2
def tree_multimap() in phasic_policy_gradient/tree_util.py	14	6	3
def process() in phasic_policy_gradient/vec_monitor2.py	18	6	1
def torch_setup() in phasic_policy_gradient/torch_util.py	17	5	2
def gather_roller_stats() in phasic_policy_gradient/log_save_helper.py	19	5	2
def aux_train() in phasic_policy_gradient/ppg.py	21	5	6
def minibatch_gen() in phasic_policy_gradient/minibatch_optimize.py	12	5	5
def multi_step() in phasic_policy_gradient/roller.py	22	5	3
def batch_len() in phasic_policy_gradient/torch_util.py	9	4	1
def NormedLinear() in phasic_policy_gradient/torch_util.py	12	4	4
def flatten_tensors() in phasic_policy_gradient/torch_util.py	8	4	3
def sync_params() in phasic_policy_gradient/torch_util.py	12	4	5
def forward() in phasic_policy_gradient/ppg.py	17	4	4
def __eq__() in phasic_policy_gradient/tree_util.py	9	4	2
def plot_data_mean_std() in phasic_policy_gradient/graph_util.py	13	4	5
def train_with_losses_and_opt() in phasic_policy_gradient/ppo.py	18	4	3
def single_step() in phasic_policy_gradient/roller.py	19	4	2
def have_cuda() in phasic_policy_gradient/torch_util.py	4	3	0
def _get_local_rank_size() in phasic_policy_gradient/torch_util.py	11	3	1
def explained_variance() in phasic_policy_gradient/torch_util.py	13	3	3
def warn_no_gradient() in phasic_policy_gradient/torch_util.py	4	3	2
def __call__() in phasic_policy_gradient/log_save_helper.py	10	3	1
def _flatten() in phasic_policy_gradient/log_save_helper.py	2	3	1
def _nanmoments_local() in phasic_policy_gradient/log_save_helper.py	8	3	2
def get_procgen_venv() in phasic_policy_gradient/envs.py	8	3	5
def make_minibatches() in phasic_policy_gradient/ppg.py	9	3	2
def main() in phasic_policy_gradient/graph.py	14	3	0
def _fmt_row() in phasic_policy_gradient/minibatch_optimize.py	5	3	3
def dict_mean() in phasic_policy_gradient/minibatch_optimize.py	2	3	1
def writeseq() in phasic_policy_gradient/logger.py	8	3	2
def writekvs() in phasic_policy_gradient/logger.py	6	3	2
def profile_kv() in phasic_policy_gradient/logger.py	11	3	2
def profile() in phasic_policy_gradient/logger.py	16	3	1