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@agrotov agrotov commented Sep 13, 2022

Description

Added params and buffers as explicit arguments to the forward functions.

Motivation and Context

Motivation
For functional evaluation, we pass the module params (and possibly buffers) together with the inputs of the module (stored in a TensorDict) using

def forward(self, tensordict, **kwargs):
params = kwargs.get("params", None)
buffers = kwargs.get("buffers", None)
...
However, this breaks when using higher.

We should have default values for these instead of using get("params", None) etc.

The changes should be compatible with: TensorDictModule, TensorDictSequence and ProbabilisticTensorDict.

close #419

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  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds core functionality)
  • Breaking change (fix or feature that would cause existing functionality to change)
  • Documentation (update in the documentation)
  • Example (update in the folder of examples)

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  • My change requires a change to the documentation.
  • I have updated the tests accordingly (required for a bug fix or a new feature).
  • I have updated the documentation accordingly.

@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Sep 13, 2022
@agrotov agrotov marked this pull request as draft September 13, 2022 08:41
@vmoens vmoens changed the title Explicit params and buffers [BugFix] Explicit params and buffers Sep 13, 2022
@vmoens vmoens added the bug Something isn't working label Sep 13, 2022
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Wonderful! Thanks for this!

to include TensorDictBase as a possibility
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Fixed types!

@agrotov agrotov marked this pull request as ready for review September 13, 2022 17:24
@vmoens vmoens merged commit 9648aa0 into pytorch:main Sep 13, 2022
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[Feature Request] Make params and buffers explicit kwargs in TensorDictModule.forward and sub-classes
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