[BugFix] Allow expanding TensorDictPrimer transforms shape with parent batch size #2521
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/rl/2521
Note: Links to docs will display an error until the docs builds have been completed. ❌ 16 New Failures, 5 Unrelated FailuresAs of commit 82c12e4 with merge base a70b258 ( NEW FAILURES - The following jobs have failed:
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LGTM, just a couple of things:
Since this will affect the transform in-place I think it should be documented in the docstrings of the class. Also, we should quickly test that the behaviour is as such, to make sure we don't modify it inadvertently in the future.
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I have remove the line where I first tried to set the primer batch_size to the parent batch_size. I could see edge cases where the batch_size could be set but still the specs needed to be expanded with and extra dimension. For example in the test I added. |
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Description
Often, when defining
TensorDictPrimertransforms during environment creation, the batch size is unknown. For example when we create the transform with thetorchrl.modules.utils.get_primers_from_modulemethod.In
TensorDictPrimer, we assume that if the parent environment is batch-locked, the specs will already have the appropriate leading shape. However, this can lead to issues if the batch size is unknown at instantiation.Maybe I am missing something here, but this PR makes sure the primer matches the parent batch size during reset, expanding it if necessary.
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