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[Feature] Max Value Writer #1622

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Oct 18, 2023
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[Feature] Max Value Writer #1622

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max value writer
albertbou92 Oct 10, 2023
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max value writer
albertbou92 Oct 10, 2023
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max value writer
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Merge branch 'main' into max_val_writer
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Update torchrl/data/replay_buffers/writers.py
vmoens Oct 18, 2023
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Update torchrl/data/replay_buffers/writers.py
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albertbou92 committed Oct 11, 2023
commit b6e1be84d2b68dbcfdc178f7610e60c72b1f8748
1 change: 1 addition & 0 deletions docs/source/reference/data.rst
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Expand Up @@ -43,6 +43,7 @@ We also give users the ability to compose a replay buffer using the following co
Writer
RoundRobinWriter
TensorDictRoundRobinWriter
TensorDictMaxValueWriter

Storage choice is very influential on replay buffer sampling latency, especially in distributed reinforcement learning settings with larger data volumes.
:class:`LazyMemmapStorage` is highly advised in distributed settings with shared storage due to the lower serialisation cost of MemmapTensors as well as the ability to specify file storage locations for improved node failure recovery.
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