That would be great. I am looking forward for your PyTorch implementation of ARS. I found one here:

  
      github.com
  
  
    LAIRLAB/ARS-experiments/blob/8c832b8c5e996621469436464716234679457cbf/ars/mnist_ars.py 17
'''
Augmented random search for MNIST
Author: Anirudh Vemula
'''
from __future__ import print_function
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
from torch.autograd import Variable
from envs.mnist.mnist import MNIST
from utils.ars import *
import numpy as np
import random
import ipdb

parser = argparse.ArgumentParser(description='PyTorch MNIST Example')
# Experiment parameters


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