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Get rid of class variables in algorithmic env. (#1910)

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Make reward_shortfalls and min_length instance variables.
Fixes the TODO in algorithmic_env.py.

Co-authored-by: pzhokhov <peterz@openai.com>
This commit is contained in:
InstanceLabs
2020-05-29 23:23:44 +02:00
committed by GitHub
parent 821841c1a1
commit d8908cbf10
2 changed files with 13 additions and 24 deletions
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12
gym/envs/algorithmic/tests/test_algorithmic.py
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@@ -58,7 +58,7 @@ class TestAlgorithmicEnvInteractions(unittest.TestCase):
def test_levelup(self):
obs = self.env.reset()
# Kind of a hack
alg.algorithmic_env.AlgorithmicEnv.reward_shortfalls = []
self.env.reward_shortfalls = []
min_length = self.env.min_length
for i in range(self.env.last):
obs, reward, done, _ = self.env.step([self.RIGHT, 1, 0])
@@ -67,17 +67,11 @@ class TestAlgorithmicEnvInteractions(unittest.TestCase):
self.assertTrue(done)
self.env.reset()
if i < self.env.last-1:
self.assertEqual(
len(alg.algorithmic_env.AlgorithmicEnv.reward_shortfalls),
i+1
)
self.assertEqual(len(self.env.reward_shortfalls), i+1)
else:
# Should have leveled up on the last iteration
self.assertEqual(self.env.min_length, min_length+1)
self.assertEqual(
len(alg.algorithmic_env.AlgorithmicEnv.reward_shortfalls),
0
)
self.assertEqual(len(self.env.reward_shortfalls), 0)
def test_walk_off_the_end(self):
obs = self.env.reset()