New version 2.6.1

[benvial]

Checklist

• Used a personal fork of the feedstock to propose changes
• Bumped the build number (if the version is unchanged)
• Reset the build number to 0 (if the version changed)
• Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
• Ensured the license file is being packaged.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipe) and found some lint.

Here's what I've got...

For recipe:

• requirements: run: jaxlib=*=*cuda* must contain a space between the name and the pin, i.e. jaxlib =*=*cuda*

For recipe:

• Please depend on pytorch directly, in order to avoid forcing CUDA users to downgrade to the CPU version for no reason.
• Please depend on pytorch directly. If your package definitely requires the CUDA version, please depend on pytorch =*=cuda*.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipe) and found some lint.

Here's what I've got...

For recipe:

• requirements: run: jaxlib= *=*cuda* must contain a space between the name and the pin, i.e. jaxlib =*=*cuda*

For recipe:

• Please depend on pytorch directly, in order to avoid forcing CUDA users to downgrade to the CPU version for no reason.
• Please depend on pytorch directly. If your package definitely requires the CUDA version, please depend on pytorch =*=cuda*.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

I do have some suggestions for making it better though...

For recipe:

• Please depend on pytorch directly, in order to avoid forcing CUDA users to downgrade to the CPU version for no reason.
• Please depend on pytorch directly. If your package definitely requires the CUDA version, please depend on pytorch =*=cuda*.