#
Locking kernel/layer versions

Projects that use `setuptools` can lock the kernel versions that should be used. First specify the accepted versions in `pyproject.toml` and make sure that `kernels` is a build dependency:

    [build-system]
    requires = ["kernels", "setuptools"]
    build-backend = "setuptools.build_meta"

    [tool.kernels.dependencies]
    "kernels-community/activation" = 1

Then run `kernels lock .` in the project directory. This generates a `kernels.lock` file with the locked revisions. The locked revision will be used when loading a kernel with get_locked_kernel():

    from kernels import get_locked_kernel

    activation = get_locked_kernel("kernels-community/activation")

Note: the lock file is included in the package metadata, so it will only be visible to `kernels` after doing an (editable or regular) installation of your project.

##
Locked kernel layers

Locking is also supported for kernel layers. To use locked layers, register them with the LockedLayerRepository class:

    kernel_layer_mapping = {
        "SiluAndMul": {
            "cuda": LockedLayerRepository(
                repo_id="kernels-community/activation",
                layer_name="SiluAndMul",
            )
        }
    }

    register_kernel_mapping(kernel_layer_mapping)

Similarly, you can use the LockedFuncRepository class to lock kernel function versions:

    kernel_layer_mapping = {
        "silu_and_mul": {
            "cuda": LockedFuncRepository(
                repo_id="kernels-community/activation",
                func_name="silu_and_mul",
            )
        }
    }

    register_kernel_mapping(kernel_layer_mapping)

##
Pre-downloading locked kernels

Locked kernels can be pre-downloaded by running `kernels download .` in your project directory. This will download the kernels to your local Hugging Face Hub cache.

The pre-downloaded kernels are used by the get_locked_kernel() function. get_locked_kernel() will download a kernel when it is not pre-downloaded. If you want kernel loading to error when a kernel is not pre-downloaded, you can use the load_kernel() function instead:

    from kernels import load_kernel

    activation = load_kernel("kernels-community/activation")

Update on GitHub