FoConrad

import argparse
import numpy as np      # Version 1.13.1
import tensorflow as tf # Version 1.4.1
import mxnet as mx      # Version 1.1.0
from mxnet import gluon, nd, autograd

# From openai baselines common/tf_util
def dense(x, size, name, weight_init=None, bias=True):
    w = tf.get_variable(name + "/w", [x.get_shape()[1], size], initializer=weight_init)
    ret = tf.matmul(x, w)

FoConrad

# Policy gradient borrowed from https://github.com/pytorch/examples/

import time
import argparse
import torch
import torchvision

import numpy as np
import torchvision.transforms as transforms
import torch.nn as nn