def __do_pause_test(num_envs, envs_to_pause):
class PausableShim:
def __init__(self, num_envs):
self._running = list(range(num_envs))
@property
def num_envs(self):
return len(self._running)
def pause_at(self, idx):
self._running.pop(idx)
envs = PausableShim(num_envs)
test_recurrent_hidden_states = (torch.arange(num_envs).view(
1, num_envs, 1).expand(4, num_envs, 512))
not_done_masks = torch.arange(num_envs).view(num_envs, 1)
current_episode_reward = torch.arange(num_envs).view(num_envs, 1)
prev_actions = torch.arange(num_envs).view(num_envs, 1)
batch = {
k: torch.arange(num_envs).view(num_envs, 1, 1,
1).expand(num_envs, 3, 256, 256)
for k in ["a", "b"]
}
rgb_frames = [[idx] for idx in range(num_envs)]
(
envs,
test_recurrent_hidden_states,
not_done_masks,
current_episode_reward,
prev_actions,
batch,
rgb_frames,
) = BaseRLTrainer._pause_envs(
envs_to_pause,
envs,
test_recurrent_hidden_states,
not_done_masks,
current_episode_reward,
prev_actions,
batch,
rgb_frames,
)
expected = sorted(set(range(num_envs)) - set(envs_to_pause))
assert envs._running == expected
assert list(test_recurrent_hidden_states.size()) == [4, len(expected), 512]
assert test_recurrent_hidden_states[0, :, 0].numpy().tolist() == expected
assert not_done_masks[:, 0].numpy().tolist() == expected
assert current_episode_reward[:, 0].numpy().tolist() == expected
assert prev_actions[:, 0].numpy().tolist() == expected
assert [v[0] for v in rgb_frames] == expected
for _, v in batch.items():
assert list(v.size()) == [len(expected), 3, 256, 256]
assert v[:, 0, 0, 0].numpy().tolist() == expected
def test_eval_config():
ckpt_opts = ["VIDEO_OPTION", "[]"]
eval_opts = ["VIDEO_OPTION", "['disk']"]
ckpt_cfg = get_config(None, ckpt_opts)
assert ckpt_cfg.VIDEO_OPTION == []
assert ckpt_cfg.CMD_TRAILING_OPTS == ["VIDEO_OPTION", "[]"]
eval_cfg = get_config(None, eval_opts)
assert eval_cfg.VIDEO_OPTION == ["disk"]
assert eval_cfg.CMD_TRAILING_OPTS == ["VIDEO_OPTION", "['disk']"]
trainer = BaseRLTrainer(get_config())
assert trainer.config.VIDEO_OPTION == ["disk", "tensorboard"]
returned_config = trainer._setup_eval_config(checkpoint_config=ckpt_cfg)
assert returned_config.VIDEO_OPTION == []
trainer = BaseRLTrainer(eval_cfg)
returned_config = trainer._setup_eval_config(ckpt_cfg)
assert returned_config.VIDEO_OPTION == ["disk"]
