wingedsheep

# import os
# os.environ["THEANO_FLAGS"] = "mode=FAST_RUN,device=gpu,floatX=float32"
# import theano

# import the neural net stuff
from keras.models import Sequential
from keras import optimizers
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution1D
from keras.layers.normalization import BatchNormalization

wingedsheep

MIT License

Copyright (c) 2020 Vincent Bons

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

wingedsheep

# import os
# os.environ["THEANO_FLAGS"] = "mode=FAST_RUN,device=gpu,floatX=float32"
# import theano

# import the neural net stuff
from keras.models import Sequential
from keras import optimizers
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution1D
from keras.layers.normalization import BatchNormalization

wingedsheep

# import os
# os.environ["THEANO_FLAGS"] = "mode=FAST_RUN,device=gpu,floatX=float32"
# import theano

# import the neural net stuff
from keras.models import Sequential
from keras import optimizers
from keras.layers.core import Dense, Dropout, Activation
from keras.layers.normalization import BatchNormalization
from keras.layers.advanced_activations import LeakyReLU

wingedsheep

# import the neural net stuff
from keras.models import Sequential
from keras import optimizers
from keras.layers.core import Dense, Dropout, Activation
from keras.layers.normalization import BatchNormalization
from keras.layers.advanced_activations import LeakyReLU
from keras.regularizers import l2

# import other stuff

wingedsheep

# import the gym stuff
import gym
# import other stuff
import random
import numpy as np
# import own classes
from deepq import DeepQ

env = gym.make('CartPole-v0')

wingedsheep

# import the gym stuff
import gym
# import other stuff
import random
import numpy as np
# import own classes
from deepq import DeepQ

env = gym.make('CartPole-v0')