How to use the gym.utils.seeding function in gym
To help you get started, we’ve selected a few gym examples, based on popular ways it is used in public projects.
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eleurent / obstacle-env / obstacle_env / envs / obstacle.py View on Github 
def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def seed(self, seed=1337):
# Seed the random number generator
self.np_random, _ = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
# 产生一个随机化时需要的种子，同时返回一个np_random对象，支持后续的随机化生成操作
self.np_random, seed = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
self.np_random, seed1 = seeding.np_random(seed)
# Derive a random seed.
seed2 = seeding.hash_seed(seed1 + 1) % 2**32
pachi_py.pachi_srand(seed2)
return [seed1, seed2]def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]def _seed(self, seed=None):
self.np_random, seed = utils.seeding.np_random(seed)
return [seed]gym
Gym: A universal API for reinforcement learning environments
Package Health Score
73 / 100Popular gym functions
- gym.Env
- gym.envs.registration.register
- gym.error.Error
- gym.make
- gym.ObservationWrapper
- gym.spaces
- gym.spaces.Box
- gym.spaces.Dict
- gym.spaces.Discrete
- gym.spaces.MultiDiscrete
- gym.spaces.Tuple
- gym.utils
- gym.utils.EzPickle
- gym.utils.EzPickle.__init__
- gym.utils.seeding
- gym.utils.seeding.np_random
- gym.Wrapper
- gym.Wrapper.__init__
- gym.wrappers
- gym.wrappers.Monitor