[BugFix] DQN loss dispatch respect configured tensordict keys #1285
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facebook-github-bot
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Jun 15, 2023
| def test_dqn_notensordict(self): | ||
| @pytest.mark.parametrize("observation_key", ["observation", "observation2"]) | ||
| @pytest.mark.parametrize("reward_key", ["reward", "reward2"]) | ||
| @pytest.mark.parametrize("done_key", ["done", "done2"]) |
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do we skip the action key by design?
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No it is intended.
Atm, the action key cannot really be configured since it is used in the constructor of the DQN loss via _find_action_space(action_space).
Either I need to remove the action key from the configurable keys or the following part of the constructor must be moved until .set_keys() is called:
if action_space is None:
# infer from value net
try:
action_space = value_network.spec
except AttributeError:
# let's try with action_space then
try:
action_space = value_network.action_space
except AttributeError:
raise ValueError(self.ACTION_SPEC_ERROR)
if action_space is None:
warnings.warn(
"action_space was not specified. DQNLoss will default to 'one-hot'."
"This behaviour will be deprecated soon and a space will have to be passed."
"Check the DQNLoss documentation to see how to pass the action space. "
)
action_space = "one-hot"
self.action_space = _find_action_space(action_space)
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Description
Dispatch of
.forwardof the DQN loss module respects configured tensordict keys.Solves #1274
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