Comments (4)
FYI Launchpad has been released (https://github.com/deepmind/launchpad, https://deepmind.com/research/open-source/launchpad) and distributed acme agents using launchpad were added in 3bc0426.
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Hi miriaford!
We have only open-sourced our single-process agents. While the code that is run in our distributed agents is identical to the open-sourced agents, the former are indeed tied to Launchpad and other DeepMind infrastructure. We don’t currently have a timetable for releasing these components. We’ll update the docs accordingly. Thanks for your question and interest in Acme!
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@tomhennigan is there an example anywhere for using acme with distributed training now launchpad has been released? I'm currently using ray and it feels slower than it should (most of the overhead comes from passing the data from the server it's stored in, to the learner).
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Hi @davidireland3, I'm not aware of any (however I haven't worked much on acme). @bshahr are you aware of any examples?
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Related Issues (20)
- Missleading errors when using discrete action space with `CanonicalSpecWrapper`
- Error importing `matplotlib`
- examples seem to be broken - examples/baselines/rl_continuous HOT 1
- Use of tf.data.Dataset within tf.function HOT 1
- Library broken HOT 1
- Reverb Replay Buffers + Vectorized/Batched Environments HOT 1
- Is the last layer in distributional critic optimized (jax implementation)? HOT 1
- Reference numbers for `reverb_benchmark.py` HOT 2
- The program always executes behavior clone when running CQLLearner.
- Masked actions in MCTS agent
- Implementing HER with Replay Buffer/Reverb HOT 1
- Issue with ACME's Distributional RL Implementation
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- Use ACME with Ray Tune ASHAScheduler
- XM Docker distributed experiments don't finish cleanly
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- Is there a num_iterations argument in offline examples? HOT 2
- Gymnasium HOT 1
- Dependency trouble HOT 1
- Dependency trouble
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