Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[Feature Request] Support propagation of in-place modifications to masked tensordict to the parent tensordict. #298

Open
1 task done
benoitdescamps opened this issue Jul 19, 2022 · 0 comments · May be fixed by pytorch/tensordict#132
Open
1 task done

[Feature Request] Support propagation of in-place modifications to masked tensordict to the parent tensordict. #298

benoitdescamps opened this issue Jul 19, 2022 · 0 comments · May be fixed by pytorch/tensordict#132
Assignees
@vmoens
Labels
enhancement New feature or request

Comments

@benoitdescamps
Copy link
Contributor

benoitdescamps commented Jul 19, 2022 •
edited
Loading

Motivation

For tensors, the following apply,

x = torch.randn(3,4)
mask = [True, False, True]
y = torch.randn(2,4)
x[mask] = y

torch.testing.assert_allclose(x[mask],y)

on the other hand for tensordict

    td = TensorDict({"a": torch.randn(3, 4, 2), "b": torch.randn(3, 4)}, [3, 4])

    mask = torch.tensor([True, False, True])
    x = torch.randn(2, 4, 2)
    td[mask]["a"] = x
    torch.testing.assert_allclose(td[mask]["a"], x)

returns error AssertionError: Tensor-likes are not close!

Solution

Instead of return a new Tensordict using mask-select, we can return instead a SubTensorDict.

Checklist

  • I have checked that there is no similar issue in the repo (required)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@vmoens vmoens

Labels
enhancement New feature or request
Projects
None yet
Milestone
No milestone
Development

Successfully merging a pull request may close this issue.

[Feature] Support propagation of in-place modifications to masked tensordict riiswa/tensordict
3 participants
@vmoens @benoitdescamps @Benjamin-eecs