Sebastian Wallkötter FirefoxMetzger

## setup.sh
#!/bin/bash
mkdir -p ~/my_docker_registry_deploy_folder/certs
cd ~/my_docker_registry_deploy_folder/
docker pull registry:2
docker save -o registry.tar registry:2

## openssl.cnf
[ req ]
default_bits		= 2048
distinguished_name	= req_distinguished_name
x509_extensions	= v3_ca	# The extentions to add to the self signed cert
string_mask = utf8only

[ req_distinguished_name ]
countryName			= Country Name (2 letter code)
countryName_default		= AU
countryName_min			= 2

## generate.sh
#!/bin/bash
openssl genrsa > certs/private.key
openssl req -new -x509 -config openssl.cnf -key certs/private.key -days 10000 > certs/certificate.crt
openssl x509 -in certs/certificate.crt -text -noout

## Dockerfile
version: '3'

services:
    registry:
        image: registry:2
        ports:
            - "443:5000"
        volumes:
            - "/var/lib/boot2docker/certs:/certs"
            - "registry_data:/data"

## deploy.sh
#!/bin/bash
docker-machine scp -r . myRegistry:~
docker-machine ssh myRegistry docker load -i registry.tar
docker-machine ssh myRegistry sudo cp -r certs /var/lib/boot2docker
docker-machine ssh myRegistry docker stack deploy --compose-file=docker-compose.yml registry

## fully_connected_reader.py
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

## upload_data.py
import requests

# to be filled in by you
token = ""                      # if you have signed up at https://scoreboard-190810.appspot.com
                                # you can find it on the top left corner of the page
environment = "Test-v0"         # name of the environment the agent is for

data = {
    "name": "My Agent Name",                        # you wrote it, you get to name it =)
    "score": "1337",                                # replace with actual score

## faster_fully_connected_reader.py
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

## Residual_Layer.py
from keras.engine.topology import Layer
from keras.layers importActivation, Conv2D, Add

class Residual(Layer):
    def __init__(self, channels_in,kernel,**kwargs):
        super(Residual, self).__init__(**kwargs)
        self.channels_in = channels_in
        self.kernel = kernel

    def call(self, x):

## cifar10_res.py
'''Train a simple residual network on the CIFAR10 small images dataset.

It gets to 75% validation accuracy in 25 epochs, and 79% after 50 epochs.
(it's still underfitting at that point, though).
'''

from __future__ import print_function
import keras
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
	#!/bin/bash
	mkdir -p ~/my_docker_registry_deploy_folder/certs
	cd ~/my_docker_registry_deploy_folder/
	docker pull registry:2
	docker save -o registry.tar registry:2
	[ req ]
	default_bits = 2048
	distinguished_name = req_distinguished_name
	x509_extensions = v3_ca # The extentions to add to the self signed cert
	string_mask = utf8only

	[ req_distinguished_name ]
	countryName = Country Name (2 letter code)
	countryName_default = AU
	countryName_min = 2
	#!/bin/bash
	openssl genrsa > certs/private.key
	openssl req -new -x509 -config openssl.cnf -key certs/private.key -days 10000 > certs/certificate.crt
	openssl x509 -in certs/certificate.crt -text -noout
	version: '3'

	services:
	registry:
	image: registry:2
	ports:
	- "443:5000"
	volumes:
	- "/var/lib/boot2docker/certs:/certs"
	- "registry_data:/data"
	#!/bin/bash
	docker-machine scp -r . myRegistry:~
	docker-machine ssh myRegistry docker load -i registry.tar
	docker-machine ssh myRegistry sudo cp -r certs /var/lib/boot2docker
	docker-machine ssh myRegistry docker stack deploy --compose-file=docker-compose.yml registry
	# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	import requests

	# to be filled in by you
	token = "" # if you have signed up at https://scoreboard-190810.appspot.com
	# you can find it on the top left corner of the page
	environment = "Test-v0" # name of the environment the agent is for

	data = {
	"name": "My Agent Name", # you wrote it, you get to name it =)
	"score": "1337", # replace with actual score
	from keras.engine.topology import Layer
	from keras.layers importActivation, Conv2D, Add

	class Residual(Layer):
	def __init__(self, channels_in,kernel,**kwargs):
	super(Residual, self).__init__(**kwargs)
	self.channels_in = channels_in
	self.kernel = kernel

	def call(self, x):
	'''Train a simple residual network on the CIFAR10 small images dataset.

	It gets to 75% validation accuracy in 25 epochs, and 79% after 50 epochs.
	(it's still underfitting at that point, though).
	'''

	from __future__ import print_function
	import keras
	from keras.datasets import cifar10
	from keras.preprocessing.image import ImageDataGenerator