Python neuralnet Examples

Example #1

File: play.py Project: AoJiang/DRL

 def __init__(self):
     self.size = 50000
     self.minibatch_size = 128
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory, frames_to_skip=6)   # 5 for space invaders
     # Loading model
     self.n_net.loadModel('./models/Improved_Breakout_AS.model.weights.NN.NMem.3707295')

Example #2

 def __init__(self):
     self.size = 50000
     self.minibatch_size = 128
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory, frames_to_skip=6)  # 5 for space invaders
     # Loading model
     self.n_net.loadModel(
         './models/Improved_Breakout_AS.model.weights.NN.NMem.3707295')

Example #3

File: pretrain_main_exp.py Project: AoJiang1991/DRL

 def __init__(self):
     self.size = 100000  # memory size ~ 5Gb
     self.epsilon_step_dec = 700000  # Counter for epsilon dec. step
     self.minibatch_size = 128  # Minibatch size
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.steps = 0
     # Loading memory
     f = file('AS.memory.D.2079', 'rb')  # Change to yours memory dump name
     self.memory.D = cPickle.load(f)
     f.close()

Example #4

File: pretrain_main_exp.py Project: AoJiang/DRL

 def __init__(self):
     self.size = 100000   # memory size ~ 5Gb
     self.epsilon_step_dec = 700000   # Counter for epsilon dec. step
     self.minibatch_size = 128   # Minibatch size
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.steps = 0
     # Loading memory
     f = file('AS.memory.D.2079', 'rb')   # Change to yours memory dump name
     self.memory.D = cPickle.load(f)
     f.close()

Example #5

File: main_exp.py Project: mihir19/DRL-TensorFlow

 def __init__(self):
     self.size = 100000  # memory size ~ 5Gb
     self.epsilon_step_dec = 700000  # Counter for epsilon dec. step
     self.M = 0  # Episodes
     self.T = 0  # Sequence max length
     self.minibatch_size = 128  # Minibatch size
     self.steps = 0  # Steps counter, inc. only
     self.count = 0  # Saving counter
     self.actions_number = 4  # Left, right, up, nothing
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory, frames_to_skip=6)  # 4 in paper (5 for space invaders)

Example #6

File: main_exp.py Project: spaceuniverse/DRL-1

 def __init__(self):
     self.size = 100000  # memory size ~ 5Gb
     self.epsilon_step_dec = 700000  # Counter for epsilon dec. step
     self.M = 0  # Episodes
     self.T = 0  # Sequence max length
     self.minibatch_size = 128  # Minibatch size
     self.steps = 0  # Steps counter, inc. only
     self.count = 0  # Saving counter
     self.actions_number = 4  # Left, right, up, nothing
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory,
                    frames_to_skip=6)  # 4 in paper (5 for space invaders)

Example #7

File: human_play.py Project: AoJiang/DRL

 def __init__(self):
     self.size = 50000
     self.minibatch_size = 128
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory, frames_to_skip=6)   # 5 for space invaders

Example #8

 def __init__(self):
     self.size = 50000
     self.minibatch_size = 128
     self.n_net = neuralnet(self.minibatch_size)
     self.memory = memory(size=self.size)
     self.ale = ale(self.memory, frames_to_skip=6)  # 5 for space invaders