def build_normalizer(env: EnvWrapper) -> Dict[str, NormalizationData]:
try:
return env.normalization_data
except AttributeError:
# TODO: make this a property of EnvWrapper?
# pyre-fixme[16]: Module `envs` has no attribute `RecSim`.
if HAS_RECSIM and isinstance(env, RecSim):
return {
NormalizationKey.STATE:
NormalizationData(
dense_normalization_parameters=only_continuous_normalizer(
list(range(env.observation_space["user"].shape[0])))),
NormalizationKey.ITEM:
NormalizationData(
dense_normalization_parameters=only_continuous_normalizer(
list(range(env.observation_space["doc"]
["0"].shape[0])))),
}
return {
NormalizationKey.STATE:
NormalizationData(
dense_normalization_parameters=build_state_normalizer(env)),
NormalizationKey.ACTION:
NormalizationData(
dense_normalization_parameters=build_action_normalizer(env)),
}
def normalization_data(self):
return {
NormalizationKey.STATE:
NormalizationData(
dense_normalization_parameters=only_continuous_normalizer(
list(range(self.num_arms)), MU_LOW, MU_HIGH))
}
def build_state_normalizer(env: EnvWrapper):
if isinstance(env.observation_space, spaces.Box):
assert (
len(env.observation_space.shape) == 1
), f"{env.observation_space.shape} has dim > 1, and is not supported."
return only_continuous_normalizer(
list(range(env.observation_space.shape[0])),
env.observation_space.low,
env.observation_space.high,
)
elif isinstance(env.observation_space, spaces.Dict):
# assuming env.observation_space is image
return None
else:
raise NotImplementedError(f"{env.observation_space} not supported")