[RLlib] Actually save the optimizer state for tf learners #34252
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It turns out you can get the actual optimizer state by calling optimizer.variables for tf keras. this pr enables us to save the full optimizer state and restore it. To do this I added a new file called optimizer_name_state.txt to the checkpoint. This holds a bytestring serialized representation of the optimizer's state. It looks like the optimizer's variable state doesn't include things like the learning rate, so I still need to save those as a separate file and reconstruct the optimizer first before loading the state. Signed-off-by: Avnish <[email protected]>
avnishn
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ArturNiederfahrenhorst,
smorad,
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kouroshHakha
approved these changes
Apr 11, 2023
…ally_save_tensorflow_state
Signed-off-by: Avnish <[email protected]>
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broken tests are unrelated. the broken doc test is addressed here: |
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failing learning tests are not impacted by this pr since they are not currently on the new learner stack |
elliottower
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Apr 22, 2023
…t#34252) It turns out you can get the actual optimizer state by calling optimizer.variables for tf keras. this pr enables us to save the full optimizer state and restore it. To do this I added a new file called optimizer_name_state.txt to the checkpoint. This holds a bytestring serialized representation of the optimizer's state. It looks like the optimizer's variable state doesn't include things like the learning rate, so I still need to save those as a separate file and reconstruct the optimizer first before loading the state. --------- Signed-off-by: Avnish <[email protected]> Signed-off-by: elliottower <[email protected]>
ProjectsByJackHe
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May 4, 2023
…t#34252) It turns out you can get the actual optimizer state by calling optimizer.variables for tf keras. this pr enables us to save the full optimizer state and restore it. To do this I added a new file called optimizer_name_state.txt to the checkpoint. This holds a bytestring serialized representation of the optimizer's state. It looks like the optimizer's variable state doesn't include things like the learning rate, so I still need to save those as a separate file and reconstruct the optimizer first before loading the state. --------- Signed-off-by: Avnish <[email protected]> Signed-off-by: Jack He <[email protected]>
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It turns out you can get the actual optimizer state by calling optimizer.variables for tf keras.
this pr enables us to save the full optimizer state and restore it. To do this I added a new
file called optimizer_name_state.txt to the checkpoint. This holds a bytestring serialized
representation of the optimizer's state. It looks like the optimizer's variable state doesn't include
things like the learning rate, so I still need to save those as a separate file and
reconstruct the optimizer first before loading the state.
Signed-off-by: Avnish [email protected]
Why are these changes needed?
Related issue number
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.