wehub-resource-sync
38 lines
1008 B
Python
38 lines
1008 B
Python
import logging
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from mla.neuralnet import NeuralNet
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from mla.neuralnet.layers import Activation, Dense
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from mla.neuralnet.optimizers import Adam
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from mla.rl.dqn import DQN
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logging.basicConfig(level=logging.CRITICAL)
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def mlp_model(n_actions, batch_size=64):
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model = NeuralNet(
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layers=[Dense(32), Activation("relu"), Dense(n_actions)],
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loss="mse",
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optimizer=Adam(),
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metric="mse",
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batch_size=batch_size,
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max_epochs=1,
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verbose=False,
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)
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return model
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model = DQN(n_episodes=2500, batch_size=64)
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model.init_environment("CartPole-v0")
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model.init_model(mlp_model)
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try:
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# Train the model
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# It can take from 300 to 2500 episodes to solve CartPole-v0 problem due to randomness of environment.
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# You can stop training process using Ctrl+C signal
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# Read more about this problem: https://gym.openai.com/envs/CartPole-v0
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model.train(render=False)
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except KeyboardInterrupt:
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pass
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# Render trained model
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model.play(episodes=100)
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