Kornia import errors: check the base package, Torch and optional extras

Read the failing name precisely

Kornia documents a PyTorch dependency and optional extras for some features.1 A missing base import, a missing extra and an unavailable function are separate investigation paths.

python -m pip show kornia kornia-rs torch

Run this with the interpreter that launches the failing instance. Our proposed next step is to compare the node's declared requirements with these records, rather than applying the newest install instructions to every older workflow.

If only an optional feature is unavailable, decide whether your task uses it before changing the environment. If a symbol cannot be imported, investigate the expected API version. Preserve the exact module or function name in the report.

After a trusted import succeeds, rerun the original operation with a small image and unchanged settings. Shape, dtype or device errors belong to a runtime branch, not another missing-package attempt. Keep the previous package list and node revision so that a change can be evaluated or reversed without guessing.

Related checks

• Spandrel is installed but the model will not load: check architecture support
• Optional backend warnings: decide what blocks your workflow

Research draft. No local/GPU reproduction or independent editorial sign-off. Upstream statements and our recommendations are distinguished.