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| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| """Tests for code_tasks.""" | |
| import numpy as np | |
| import tensorflow as tf | |
| from single_task import code_tasks # brain coder | |
| from single_task import defaults # brain coder | |
| def pad(string, pad_length, pad_char): | |
| return string + pad_char * (pad_length - len(string)) | |
| class CodeTasksTest(tf.test.TestCase): | |
| def assertClose(self, a, b): | |
| self.assertTrue( | |
| np.isclose(a, b, atol=1e-4), | |
| 'Expecting approximately equal values. Got: %s, %s' % (a, b)) | |
| def testMultiIOTaskManager(self): | |
| maxlen = 100 | |
| padchr = '[' | |
| task = code_tasks.make_paper_task( | |
| 'print', timestep_limit=maxlen, do_code_simplification=False) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose( | |
| r(pad('++++++++.---.+++++++...', maxlen, padchr)).episode_rewards[-1], | |
| 0.2444) | |
| self.assertClose( | |
| r(pad('++++++++.---.+++++++..+++.', | |
| maxlen, padchr)).episode_rewards[-1], | |
| 1.0) | |
| task = code_tasks.make_paper_task( | |
| 'print', timestep_limit=maxlen, do_code_simplification=True) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose( | |
| r('++++++++.---.+++++++...').episode_rewards[-1], | |
| 0.2444) | |
| self.assertClose( | |
| r('++++++++.---.+++++++..+++.').episode_rewards[-1], | |
| 0.935) | |
| self.assertClose( | |
| r(pad('++++++++.---.+++++++..+++.', | |
| maxlen, padchr)).episode_rewards[-1], | |
| 0.75) | |
| task = code_tasks.make_paper_task( | |
| 'reverse', timestep_limit=maxlen, do_code_simplification=False) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose( | |
| r(pad('>,>,>,.<.<.<.', maxlen, padchr)).episode_rewards[-1], | |
| 0.1345) | |
| self.assertClose( | |
| r(pad(',[>,]+[,<.]', maxlen, padchr)).episode_rewards[-1], | |
| 1.0) | |
| task = code_tasks.make_paper_task( | |
| 'reverse', timestep_limit=maxlen, do_code_simplification=True) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose(r('>,>,>,.<.<.<.').episode_rewards[-1], 0.1324) | |
| self.assertClose(r(',[>,]+[,<.]').episode_rewards[-1], 0.9725) | |
| self.assertClose( | |
| r(pad(',[>,]+[,<.]', maxlen, padchr)).episode_rewards[-1], | |
| 0.75) | |
| def testMakeTask(self): | |
| maxlen = 100 | |
| padchr = '[' | |
| config = defaults.default_config_with_updates( | |
| 'env=c(config_for_iclr=False,fixed_string=[8,5,12,12,15])') | |
| task = code_tasks.make_task(config.env, 'print', timestep_limit=maxlen) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose( | |
| r('++++++++.---.+++++++...').episode_rewards[-1], | |
| 0.2444) | |
| self.assertClose( | |
| r('++++++++.---.+++++++..+++.').episode_rewards[-1], | |
| 0.935) | |
| self.assertClose( | |
| r(pad('++++++++.---.+++++++..+++.', | |
| maxlen, padchr)).episode_rewards[-1], | |
| 0.75) | |
| def testKnownCodeBaseTask(self): | |
| maxlen = 100 | |
| padchr = '[' | |
| task = code_tasks.make_paper_task( | |
| 'shift-left', timestep_limit=maxlen, do_code_simplification=False) | |
| reward_fns = task.rl_batch(1) | |
| r = reward_fns[0] | |
| self.assertClose( | |
| r(pad(',>,[.,]<.,.', maxlen, padchr)).episode_rewards[-1], | |
| 1.0) | |
| if __name__ == '__main__': | |
| tf.test.main() | |