Adam Stelmaszczyk AdamStelmaszczyk

## tensorboard_logging.py
"""Simple example on how to log scalars and images to tensorboard without tensor ops.

License: BSD License 2.0
"""
__author__ = "Michael Gygli"

import tensorflow as tf
from StringIO import StringIO
import matplotlib.pyplot as plt
import numpy as np

## bluejeans_rpm_via_alien.md

      
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              21 stars
            
          
                johnduarte
                / bluejeans_rpm_via_alien.md
            
            
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              January 30, 2020 09:28
            
              
                BlueJeans rpm install on Debian
              
          
    FYI, for those of us running Debian based systems rather than RedHat, the BlueJeans RPM can be successfully installed via alien
Steps to install BlueJeans on Debian

Download BlueJeans RPM
Install alien package sudo apt-get install alien
Convert BlueJeans RPM to a DEB package sudo alien --to-deb --scripts bluejeans-*.rpm
Install resulting DEB sudo dpkg -i bluejeans_*.deb
Run BlueJeans with /opt/bluejeans/bluejeans-bin

You may get an error loading the expected udev library

  
## README.md

      
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                robertpainsi
                / README.md
            
            
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              March 21, 2024 10:45
            
              
                How to reopen a pull-request after a force-push?
              
          
    How to reopen a pull-request after a force-push?

Precodinitions


You need the rights to reopen pull requests on the repository.
The pull request hasn't been merged, just closed.

Instructions


Write down the current commit hash of your PR-branch git log --oneline -1 <PR-BRANCH>
Write down the latest commit hash on github before the PR has been closed.
git push -f origin :


## pg-pong.py
""" 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

## optimizely.js
"use strict";

//based on https://www.optimizely.com/resources/sample-size-calculator/
function getSampleSize() {
    let effect = 0.05; // Minimum Detectable Effect
    let significance = 0.95; // Statistical Significance
    let conversion = 0.05; // Baseline Conversion Rate

    let c = conversion - (conversion * effect);
    let p = Math.abs(conversion * effect);

## results.txt
Data Size:
  Input:  2074
  LZ4:    758 (0.37)
  Snappy: 676 (0.33)
  LZF:    697 (0.34)
  ZLIB:   510 (0.25)
  LZ4 / Snappy: 1.121302
  LZ4 / LZF:    1.087518
  LZ4 / ZLIB:   1.486275
Benchmark: 50000 calls
	"""Simple example on how to log scalars and images to tensorboard without tensor ops.

	License: BSD License 2.0
	"""
	__author__ = "Michael Gygli"

	import tensorflow as tf
	from StringIO import StringIO
	import matplotlib.pyplot as plt
	import numpy as np
	""" 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
	"use strict";

	//based on https://www.optimizely.com/resources/sample-size-calculator/
	function getSampleSize() {
	let effect = 0.05; // Minimum Detectable Effect
	let significance = 0.95; // Statistical Significance
	let conversion = 0.05; // Baseline Conversion Rate

	let c = conversion - (conversion * effect);
	let p = Math.abs(conversion * effect);
	Data Size:
	Input: 2074
	LZ4: 758 (0.37)
	Snappy: 676 (0.33)
	LZF: 697 (0.34)
	ZLIB: 510 (0.25)
	LZ4 / Snappy: 1.121302
	LZ4 / LZF: 1.087518
	LZ4 / ZLIB: 1.486275
	Benchmark: 50000 calls