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# 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, |
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""" | |
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) |
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""" | |
Vanilla Char-RNN using TensorFlow by Vinh Khuc (@knvinh). | |
Adapted from Karpathy's min-char-rnn.py | |
https://gist.github.com/karpathy/d4dee566867f8291f086 | |
Requires tensorflow>=1.0 | |
BSD License | |
""" | |
import random | |
import numpy as np | |
import tensorflow as tf |
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""" | |
This is a batched LSTM forward and backward pass | |
""" | |
import numpy as np | |
import code | |
class LSTM: | |
@staticmethod | |
def init(input_size, hidden_size, fancy_forget_bias_init = 3): |
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# After Ubuntu 16.04, Systemd becomes the default. | |
# It is simpler than https://gist.github.com/Doowon/38910829898a6624ce4ed554f082c4dd | |
[Unit] | |
Description=Jupyter Notebook | |
[Service] | |
Type=simple | |
PIDFile=/run/jupyter.pid | |
ExecStart=/home/phil/Enthought/Canopy_64bit/User/bin/jupyter-notebook --config=/home/phil/.jupyter/jupyter_notebook_config.py |
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""" 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 |