protoget

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

protoget

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

protoget

ps server

import tensorflow as tf

cluster = tf.train.ClusterSpec({"ps": ['localhost:2222'], "worker": ['localhost:2224','localhost:2225']})
server = tf.train.Server(cluster.as_cluster_def(), job_name='ps', task_index=0)

server.join()