TAXONS  0.1
Task Agnostic eXploration of Outcome spaces through Novelty and Surprise
train Namespace Reference

Functions

def main (seed, params)
 

Variables

 enabled
 
 p = parameters.Params()
 
 parallel_threads = p.threads
 
list seeds
 
list multiseeds = []
 
int total_train_time = 0
 
list params = [parameters.Params() for i in range(len(seeds))]
 
 nodes = min(len(seeds), pathos.threading.cpu_count()-1)
 
 start_time = time.monotonic()
 
 results = pool.map(main, seeds, params)
 
 end_time = time.monotonic()
 
bool end = False
 

Function Documentation

def train.main (   seed,
  params 
)

Variable Documentation

train.enabled
bool train.end = False
train.end_time = time.monotonic()
list train.multiseeds = []
train.nodes = min(len(seeds), pathos.threading.cpu_count()-1)
train.p = parameters.Params()
train.parallel_threads = p.threads
list train.params = [parameters.Params() for i in range(len(seeds))]
train.results = pool.map(main, seeds, params)
list train.seeds
Initial value:
1 = [11, 59,
2  3, 6, 4,
3  18, 13, 1,
4  22, 34, 99,
5  43, 100, 15,
6  66, 10,7,
7  9, 42, 2
8  ]
train.start_time = time.monotonic()
int train.total_train_time = 0