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10 def seed(self, value): 11 self.engine.seed(value) 12 self.distribution.reset()
266 def seed(self): 267 import random 268 import numpy as np 269 import tensorflow as tf 270 self.flags.seed = self.flags.seed or np.random.randint(1000000) 271 random.seed(self.flags.seed) 272 np.random.seed(self.flags.seed)
24 def set_random_seed(seed): 25 # set Python random seed 26 random.seed(seed) 27 # set NumPy random seed 28 np.random.seed(seed)
680 def init_random(self): 681 682 """ 683 desc: 684 Initializes the random number generators. For some reason, the numpy 685 random seed is not re-initialized when the experiment is started 686 again with the multiprocess runner, resulting in identical random 687 runs. The standard random module doesn't suffer from this problem. 688 But to be on the safe side, we now explicitly re-initialize the 689 random seed. 690 691 See also: 692 693 - 694 """ 695 696 import random 697 random.seed() 698 try: 699 # Don't assume that numpy is available 700 import numpy 701 numpy.random.seed() 702 except: 703 pass
34 def seed(seed=None): 35 np.random.seed(seed)
22 def get_random_seed(): 23 """Generate a random int good for seeding RNG via `seed` function""" 24 return int(np.random.uniform()*(2**31-1))
47 def seed(self, x = 0, y = 0, z = 0): 48 """Set the seed from (x, y, z). 49 These must be integers in the range [0, 256).""" 50 if not type(x) == type(y) == type(z) == type(0): 51 raise TypeError, 'seeds must be integers' 52 if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256): 53 raise ValueError, 'seeds must be in range(0, 256)' 54 if 0 == x == y == z: 55 # Initialize from current time 56 import time 57 t = long(time.time() * 256) 58 t = int((t&0xffffff) ^ (t>>24)) 59 t, x = divmod(t, 256) 60 t, y = divmod(t, 256) 61 t, z = divmod(t, 256) 62 # Zero is a poor seed, so substitute 1 63 self._seed = (x or 1, y or 1, z or 1)
36 def set_seed_random(seed): 37 random.seed(seed) 38 np.random.seed(seed) 39 if chainer.cuda.available: 40 chainer.cuda.cupy.random.seed(seed)
31 def __init__(self, seed): 32 self._seed = seed 33 self._master_rng_fct = rand.RandomState(seed) 34 self._master_rng = lambda: self._master_rng_fct.randint(1, 2 ** 16)
140 def set_seed(self, val): 141 """Set current PRNG seed.""" 142 self._streams = {} 143 self._seed = val