[FEATURE] TensorDictModule in_keys allowed as Dict[str, tuple | list] to enable multi use of a sample feature #1101
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Hello, thanks for this PR!
IIUC your change is to allow one element of the input tensordict to be used multiple times within the module inputs.
That would be a good addition.
I think the tests would need to be a bit more extensive. We also need to check this works with other TD modules, like ProbabilisticTensorDictModule.
test/test_nn.py
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| def test_tuple_input_keys(self): | ||
| in_keys = {"1": "first", "2": ("second", "third")} | ||
| fn = lambda x, y, z: x + y + z | ||
| module = TensorDictModule(fn, in_keys=in_keys, out_keys=["out"]) | ||
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| kword_in_keys = sorted(zip(module._kwargs, module.in_keys)) | ||
| assert kword_in_keys == [("first", "1"), ("second", "2"), ("third", "2")] |
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I don't really get this example:
the modue is not run, what would the input tensordict look like?
Could the example be a bit more extensive?
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Thanks, it's a good point - I updated that test. I also added another test that tests the integration of TensorDictModule within a ProbabilisticTensorDictSequential.
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@vmoens Thanks for your feedback.
Could you clarify how you would see the change with ProbabilisticTensorDictModule? It seems to me that this feature will only impact TensorDictModule. ProbabilisticTensorDictModule inherits from TensorDictModuleBase and is not affected. Also I don't see the use of implementing my suggested feature in ProbabilisticTensorDictModule - its input have to be unique as far I see it.
Please let me know your thoughts
… flexible input key dispatching
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Description
See feature request #1099
Motivation and Context
Close issue #1099
Types of changes
Checklist