[RLlib] added preprocessor to dataset #28420
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Signed-off-by: Kourosh Hakhamaneshi <[email protected]>
kouroshHakha
requested review from
sven1977,
gjoliver,
avnishn,
ArturNiederfahrenhorst,
smorad,
maxpumperla and
krfricke
as code owners
Signed-off-by: Kourosh Hakhamaneshi <[email protected]>
Signed-off-by: Kourosh Hakhamaneshi <[email protected]>
gjoliver
reviewed
Sep 10, 2022
rllib/offline/dataset_reader.py
Outdated
| samples = [] | ||
| for sample in batch[key]: | ||
| samples.append(preprocessor.transform(sample)) | ||
| batch[key] = np.stack(samples, axis=0) |
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batch[key] = np.stack([preprocessor.transform(s) for s in batch[key]])
| ret.append(self._postprocess_if_needed(d)) | ||
| ret = concat_samples(ret) | ||
| return ret | ||
|
|
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| def _preprocess_if_needed(self, batch: SampleBatchType) -> SampleBatchType: | ||
| # TODO: @kourosh, preprocessor is only supported for single agent case. |
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seems like I can replace all of these with connectors after it's enabled by default.
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sg, this was not supported properly yet. So let's continue with this solution for now.
| count += d.count | ||
| d = self._preprocess_if_needed(d) |
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should we re-arrange these to be:
...
count += d.count
d = self._preprocess_if_needed(d)
d = postprocess_actions(d, self._ioctx.worker)
d = self._postprocess_if_needed(d)
ret.append(d)
so it looks like preprocessing happens before postprocessing??
Signed-off-by: Kourosh Hakhamaneshi <[email protected]>
Signed-off-by: Kourosh Hakhamaneshi <[email protected]>
|
@gjoliver I addressed all your comments. |
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Signed-off-by: Kourosh Hakhamaneshi [email protected]
Why are these changes needed?
Dataset reader does not apply rllib preprocessors if the observation space is complex.
Related issue number
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git commit -s) in this PR.scripts/format.shto lint the changes in this PR.