Skip to content

Conversation

@justincdavis
Copy link

Summary

Implements the CV-CUDA backend kernel for invert

Testing

python3 -m pytest test/test_transforms_v2.py::TestInvert

@pytorch-bot
Copy link

pytorch-bot bot commented Dec 2, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/vision/9290

Note: Links to docs will display an error until the docs builds have been completed.

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

❌ 5 New Failures

As of commit 637b4c4 with merge base aa35ca1 (image):

NEW FAILURES - The following jobs have failed:

This comment was automatically generated by Dr. CI and updates every 15 minutes.

@meta-cla meta-cla bot added the cla signed label Dec 2, 2025
Copy link
Contributor

@zy1git zy1git left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I left a comment as the first round review. Feel free to let me know your thoughts.

# we save these here, since they are static and small in size
if "base" not in _invert_cvcuda_tensors:
_invert_cvcuda_tensors["base"] = cvcuda.as_tensor(
torch.tensor([0.0, 0.0, 0.0], dtype=torch.float32, device="cuda").reshape(1, 1, 1, 3).contiguous(), "NHWC"
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

The base and scale tensors are hardcoded for 3 channels (RGB). The current CV-CUDA tests only use the default color_space="RGB", so they wouldn't catch issues with grayscale (1 channel). Is this a problem?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants