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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.7.2/Chart.bundle.min.js"></script>
<div style="width:400px;">
  <canvas id="myChart" width="400" height="400"></canvas>
</div>

<button onclick="train()">Train the model 1 step</button>
<script>
  const trainX = [
    3.3,

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##############################################################
# Calculate the average reward of a set of runs by averaging all the runs, similar to the contest scoring
# 
# $ python3 ./scripts/calc_reward.py jerk-agentv12
# 99.900000% done, reward: 6970.131268
# 
# https://medium.com/@tristansokol/making-fun-visuals-history-maps-and-other-tool-improvements-eb5ffe187fd3
############################################################## 

import numpy as np

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<script>
export default {
  name: "paymentForm",
  data: function() {
    return {
      errors: [],
      masterpass: false,
      applePay: false
    };
  },

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<template>
<div>
  <div id="sq-ccbox">
    <!--
      You should replace the action attribute of the form with the path of
      the URL you want to POST the nonce to (for example, "/process-card")
    -->
    <form id="nonce-form" novalidate action="path/to/payment/processing/page" method="post">
      <div class="errorbox">
        <div class="error" v-for="error in errors">

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$ python -m venv projectname
$ source projectname/bin/activate
(venv) $ pip install ipykernel
(venv) $ ipython kernel install --user --name=projectname
(venv) jupyter notebook
# Kernel > Change Kernel > projectname

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Array.prototype.map.call( document.querySelectorAll('a.mr-3[href*="stargazers"]'), function(n){
return Number(n.text.replace(',',''))
}).reduce(function(total,num){return total+num});

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#!/usr/bin/python

import sys
import retro
import numpy as np
from os import listdir
from os.path import isfile, join, isdir, dirname, realpath
from PIL import Image

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import numpy as np
import os
dir_path = os.getcwd()

import sys
firstarg=sys.argv[1]

r, _, _ = np.loadtxt(dir_path+'/results/'+firstarg+'/monitor.csv', delimiter=',', unpack=True, skiprows=1)
l, _ = np.loadtxt(dir_path+'/results/'+firstarg+'/log.csv', delimiter=',', unpack=True, skiprows=1)
print('%f%% done, reward: %f' % (max(l)/10000 ,np.mean(r)))

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import matplotlib.pyplot as plt
import numpy as np
import os
dir_path = os.getcwd()

r, l, t = np.loadtxt(dir_path+'/results/jerk-agentv10/monitor.csv', delimiter=',', unpack=True, skiprows=1)
fig = plt.figure(num=None, figsize=(14, 6), dpi=80, facecolor='w', edgecolor='k')

ax  = fig.add_subplot(111)
ax.plot(t, r, c='b', label='Reward',linewidth=0.5)