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31 lines
1.0 KiB
Python
31 lines
1.0 KiB
Python
import random
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import numpy as np
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from gym.envs.algorithmic import algorithmic_env
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from gym.envs.algorithmic.algorithmic_env import ha
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class ReversedAdditionEnv(algorithmic_env.AlgorithmicEnv):
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def __init__(self, rows=2, base=3):
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self.rows = rows
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algorithmic_env.AlgorithmicEnv.__init__(self,
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inp_dim=2,
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base=base,
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chars=False)
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def set_data(self):
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self.content = {}
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self.target = {}
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curry = 0
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for i in range(self.total_len):
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vals = []
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for k in range(self.rows):
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val = random.randrange(self.base)
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self.content[ha(np.array([i, k]))] = val
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vals.append(val)
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total = sum(vals) + curry
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self.target[i] = total % self.base
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curry = total / self.base
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if curry > 0:
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self.target[self.total_len] = curry
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self.total_reward = self.total_len
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