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| 1 | +#! /usr/bin/env python |
| 2 | + |
1 | 3 | import unittest |
2 | 4 | import gym |
3 | 5 | import sys |
|
21 | 23 | from policy_monitor import PolicyMonitor |
22 | 24 | from worker import Worker |
23 | 25 |
|
24 | | -tf.flags.DEFINE_string("model_dir", "/tmp/a3c", "Directory to write to") |
25 | | -tf.flags.DEFINE_string("env", "Breakout-v0", "Name of gym Atari environment") |
| 26 | +tf.flags.DEFINE_string("model_dir", "/tmp/a3c", "Directory to write Tensorboard summaries and videos to.") |
| 27 | +tf.flags.DEFINE_string("env", "Breakout-v0", "Name of gym Atari environment, e.g. Breakout-v0") |
26 | 28 | tf.flags.DEFINE_integer("t_max", 5, "Number of steps before performing an update") |
27 | | -tf.flags.DEFINE_integer("max_global_steps", None, "Stop after this many steps in the environment") |
| 29 | +tf.flags.DEFINE_integer("max_global_steps", None, "Stop training after this many steps in the environment. Defaults to running indefinitely.") |
28 | 30 | tf.flags.DEFINE_integer("eval_every", 300, "Evaluate the policy every N seconds") |
29 | | -tf.flags.DEFINE_boolean("reset", False, "If true, delete the existing model directory") |
| 31 | +tf.flags.DEFINE_boolean("reset", False, "If set, delete the existing model directory and start training from scratch.") |
30 | 32 | tf.flags.DEFINE_integer("parallelism", None, "Number of threads to run. If not set we run [num_cpu_cores] threads.") |
31 | 33 |
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32 | 34 | FLAGS = tf.flags.FLAGS |
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