for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
# Author: Simon Blanke
# Email: [email protected]
# License: MIT License
import random
import numpy as np
def set_random_seed(nth_process, random_state):
"""
Sets the random seed separately for each thread
(to avoid getting the same results in each thread)
if nth_process is None:
nth_process = 0
if random_state is None:
random_state = np.random.randint(0, high=2 ** 31 - 2, dtype=np.int64)
random.seed(random_state + nth_process)
np.random.seed(random_state + nth_process)
def move_random(ss_positions):
position = []
for search_space_pos in ss_positions:
pos_ = random.choice(search_space_pos)
position.append(pos_)
return np.array(position)
SimonBlanke /
Gradient-Free-Optimizers
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