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This issue is a list of contributions requests from the community.
How to use this list
If you're willing to contribute to the library, have a look at the list below and don't hesitate to pick up a task.
If you need guidance, refer to @vmoens for more information!
Once you pick up a task, assign the related issue to yourself, to make sure that no other collaborator is working on the same task at the same time (or create an issue if there isn't one already).
If you want to add an item to this list, start by raising an issue and mention that you think it would be appropriate to put it in the "call for contributions" stack.
New algorithms can be coded either in a free form or using torchrl's trainer class.
In any case, we would ask to the user to use hydra for the configuration, and to limit the number of extra dependencies as much as can be.
Add an option to "squash" the observation dictionary in register_gym when there is only one observation (ie, not return a dict but a simple tensor)
Add a num_envs option in DMControlEnv to create a parallel env in just one call, e.g. DMControlEnv(name, task, num_envs=4) would run 4 parallel envs of the name, task dmc env.
This issue is a list of contributions requests from the community.
How to use this list
If you're willing to contribute to the library, have a look at the list below and don't hesitate to pick up a task.
If you need guidance, refer to @vmoens for more information!
Once you pick up a task, assign the related issue to yourself, to make sure that no other collaborator is working on the same task at the same time (or create an issue if there isn't one already).
If you want to add an item to this list, start by raising an issue and mention that you think it would be appropriate to put it in the "call for contributions" stack.
If it's your first contribution, warm up with an issue marked with https://github.com/github/docs/labels/Good%20first%20issue label (and claim the issue so no one else does!)
New algorithms
New algorithms can be coded either in a free form or using torchrl's trainer class.
In any case, we would ask to the user to use hydra for the configuration, and to limit the number of extra dependencies as much as can be.
## New environment libraries
New modules and features
register_gym
when there is only one observation (ie, not return a dict but a simple tensor)num_envs
option in DMControlEnv to create a parallel env in just one call, e.g.DMControlEnv(name, task, num_envs=4)
would run 4 parallel envs of thename, task
dmc env.Datasets
BugFixes
FlattenObservation
transform withOneHotDiscreteTensorSpec
#1904Deprecation calls
rl/torchrl/modules/tensordict_module/exploration.py
Line 252 in 69d44f5
rl/torchrl/modules/tensordict_module/exploration.py
Line 385 in 69d44f5
rl/torchrl/modules/tensordict_module/exploration.py
Line 31 in 69d44f5
Solved issues
Thanks for contributing to TorchRL!
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