| # Copyright 2018 The TensorFlow Probability Authors. | |
| # | |
| # 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, |
Create file /etc/systemd/system/docker-compose@.service. SystemD calling binaries using an absolute path. In my case is prefixed by /usr/local/bin, you should use paths specific for your environment.
| # Copyright 2016 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, |
| # Copyright 2016 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, |
| ''' | |
| #### simple = True enables overriding behaviour | |
| #### modifed from tensorflow_probability == 0.3.0 | |
| ''' | |
| # Copyright 2016 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 |
| # Pkg.clone("https://github.com/JuliaLang/Pkg3.jl.git") | |
| PKG = [ | |
| "IJulia", | |
| "Combinatorics", | |
| "Plots", | |
| "TaylorSeries", | |
| "Distributions", | |
| "Cubature", | |
| "Playground"] | |
| Pkg.add.(PKG) |
| #### Pattern count | |
| #### A simple demo of for-loop and logic | |
| #### From https://stackoverflow.com/questions/26703321/python-pattern-count-find-a-hidden-message-in-the-replication-origin | |
| #### Save this text in a file named "demo.py" and issue in command line " python demo.py ", this script is compatible with python2 only. | |
| #### Check your python version with " python --version " | |
| def pattern_count(text, pattern): | |
| count = 0 | |
| for i in range(0, len(text) - len(pattern) + 1): |
| """ 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 |
