Created
July 25, 2017 08:20
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OpenAI CartPole w/ Keras: Prediction
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""" | |
__name__ = predict.py | |
__author__ = Yash Patel | |
__description__ = Does the prediction using the defined model and data | |
""" | |
import gym | |
import numpy as np | |
from data import gather_data | |
from model import create_model | |
def predict(): | |
env = gym.make("CartPole-v0") | |
trainingX, trainingY = gather_data(env) | |
model = create_model() | |
model.fit(trainingX, trainingY, epochs=5) | |
scores = [] | |
num_trials = 50 | |
sim_steps = 500 | |
for trial in range(num_trials): | |
observation = env.reset() | |
score = 0 | |
for step in range(sim_steps): | |
action = np.argmax(model.predict(observation.reshape(1,4))) | |
observation, reward, done, _ = env.step(action) | |
score += reward | |
if done: | |
break | |
scores.append(score) | |
print(np.mean(scores)) | |
if __name__ == "__main__": | |
predict() |
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