Set version to 0.10.3

* feat: allow kernels to be uploaded to a revision

* revision -> branch

.github/workflows/test.yml

@@ -24,7 +24,7 @@ jobs:
       max-parallel: 4
       matrix:
         python-version: ["3.10", "3.12"]
-        torch-version: ["2.6.0", "2.7.0"]
+        torch-version: ["2.7.0", "2.8.0"]
 
     env:
       UV_PYTHON_PREFERENCE: only-managed
@@ -51,11 +51,16 @@ jobs:
         run: uv run mypy src/kernels
 
       - name: Run tests
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
         run: |
           uv run pytest tests
 
+      - name: Run staging tests
+        env:
+          HF_TOKEN: ${{ secrets.HF_STAGING_TOKEN }}
+        run: |
+          HUGGINGFACE_CO_STAGING=true uv run pytest --token -m "is_staging_test" tests/
+        if: matrix.python_version == '3.10' && matrix.torch-version == '2.7.0'
+
       - name: Check kernel conversion
         run: |
           uv pip install wheel
@@ -68,6 +73,11 @@ jobs:
         run: |
           uv run kernels generate-readme kernels-community/triton-layer-norm
 
+      - name: Check kernel check
+        run: |
+          uv pip install kernel-abi-check
+          kernels check kernels-community/activation
+
       - name: Import check without torch
         run: |
           uv pip uninstall torch

Makefile

@@ -0,0 +1,8 @@
+.PHONY: style
+
+export check_dirs := src examples tests
+
+style:
+	black ${check_dirs}
+	isort ${check_dirs}
+	ruff check ${check_dirs} --fix

docs/source/api/kernels.md

@@ -6,6 +6,10 @@
 
 [[autodoc]] kernels.get_kernel
 
+### get_local_kernel
+
+[[autodoc]] kernels.get_local_kernel
+
 ### has_kernel
 
 [[autodoc]] kernels.has_kernel

docs/source/api/layers.md

@@ -39,3 +39,11 @@
 ### LayerRepository
 
 [[autodoc]] kernels.LayerRepository
+
+### LocalLayerRepository
+
+[[autodoc]] kernels.LocalLayerRepository
+
+### LockedLayerRepository
+
+[[autodoc]] kernels.LockedLayerRepository

docs/source/cli.md

@@ -2,6 +2,24 @@
 
 ## Main Functions
 
+### kernels check
+
+You can use `kernels check` to test compliance of a kernel on the Hub.
+This currently checks that the kernel:
+
+- Supports the currently-required Python ABI version.
+- Works on supported operating system versions.
+
+For example:
+
+```bash
+$ kernels check kernels-community/flash-attn3
+Checking variant: torch28-cxx11-cu128-aarch64-linux
+  🐍 Python ABI 3.9 compatible
+  🐧 manylinux_2_28 compatible
+[...]
+```
+
 ### kernels to-wheel
 
 We strongly recommend downloading kernels from the Hub using the `kernels`
@@ -30,7 +48,7 @@ $ kernels to-wheel drbh/img2grey 1.1.2
 ### kernels upload
 
 Use `kernels upload <dir_containing_build> --repo_id="hub-username/kernel"` to upload
-your kernel builds to the Hub.
+your kernel builds to the Hub. To know the supported arguments run: `kernels upload -h`.
 
 **Notes**:
 
@@ -38,4 +56,3 @@ your kernel builds to the Hub.
 - If a repo with the `repo_id` already exists and if it contains a `build` with the build variant
   being uploaded, it will attempt to delete the files existing under it.
 - Make sure to be authenticated (run `hf auth login` if not) to be able to perform uploads to the Hub.
-

docs/source/faq.md

@@ -1,6 +1,8 @@
 # FAQ
 
-## Why is the kernelization step needed?
+## Kernel layers
+
+### Why is the kernelization step needed as a separate step?
 
 In earlier versions of `kernels`, a layer's `forward` method was replaced
 by `use_kernel_forward_from_hub` and `replace_kernel_forward_from_hub`.
@@ -11,3 +13,29 @@ on data-dependent branching.
 
 To avoid branching, we have to make dispatch decisions ahead of time,
 which is what the `kernelize` function does.
+
+### Why does kernelization only replace `forward` methods?
+
+There are some other possible approaches. The first is to completely
+replace existing layers by kernel layers. However, since this would
+permit free-form layer classes, it would be much harder to validate
+that layers are fully compatible with the layers that they are
+replacing. For instance, they could have completely different member
+variables. Besides that, we would also need to hold on to the original
+layers, in case we need to revert to the base layers when the model
+is `kernelize`d again with different options.
+
+A second approach would be to make an auxiliary layer that wraps the
+original layer and the kernel layer and dispatches to the kernel layer.
+This wouldn't have the issues of the first approach, because kernel layers
+could be similarly strict as they are now, and we would still have access
+to the original layers when `kernelize`-ing the model again. However,
+this would change the graph structure of the model and would break use
+cases where programs access the model internals (e.g.
+`model.layers[0].attention.query_weight`) or rely on the graph structure
+in other ways.
+
+The approach of `forward`-replacement is the least invasive, because
+it preserves the original model graph. It is also reversible, since
+even though the `forward` of a layer _instance_ might be replaced,
+the corresponding class still has the original `forward`.

docs/source/kernel-requirements.md

@@ -46,6 +46,16 @@ have dynamic library dependencies outside:
 - Torch;
 - CUDA/ROCm libraries installed as dependencies of Torch.
 
+## Compatibility with torch.compile
+
+The Kernel Hub also encourages to write the kernels in a `torch.compile`
+compliant way. This helps to ensure that the kernels are compatible with
+`torch.compile` without introducing any graph breaks and triggering 
+recompilation which can limit the benefits of compilation.
+
+[Here](https://github.com/huggingface/kernel-builder/blob/d1ee9bf9301ac8c5199099d90ee1c9d5c789d5ba/examples/relu-backprop-compile/tests/test_relu.py#L162) is a simple test example which checks for graph breaks and 
+recompilation triggers during `torch.compile`.
+
 ### Linux
 
 - Use [ABI3/Limited API](https://docs.python.org/3/c-api/stable.html#stable-application-binary-interface)

examples/basic.py

@@ -20,11 +20,11 @@ activation.gelu_fast(y, x)
 print("Kernel successfully executed")
 
 # Check results
-expected = torch.tensor([
-    [0.8408, 1.9551, 2.9961],
-    [4.0000, 5.0000, 6.0000],
-    [7.0000, 8.0000, 9.0000]
-], device='cuda:0', dtype=torch.float16)
+expected = torch.tensor(
+    [[0.8408, 1.9551, 2.9961], [4.0000, 5.0000, 6.0000], [7.0000, 8.0000, 9.0000]],
+    device="cuda:0",
+    dtype=torch.float16,
+)
 assert torch.allclose(y, expected)
 
 print("Calculated values are exact")

flake.nix

@@ -24,6 +24,7 @@
       in
       {
         formatter = pkgs.nixfmt-tree;
+        packages.kernel-abi-check = pkgs.python3.pkgs.callPackage ./nix/kernel-abi-check.nix {};
         devShells = with pkgs; rec {
           default = mkShell {
             nativeBuildInputs = [
@@ -40,6 +41,7 @@
               ++ (with python3.pkgs; [
                 docutils
                 huggingface-hub
+                (callPackage ./nix/kernel-abi-check.nix {})
                 mktestdocs
                 pytest
                 pytest-benchmark

nix/kernel-abi-check.nix

@@ -0,0 +1,27 @@
+{
+  buildPythonPackage,
+  fetchPypi,
+  rustPlatform,
+}:
+
+buildPythonPackage rec {
+  pname = "kernel-abi-check";
+  version = "0.6.2";
+
+  src = fetchPypi {
+    inherit version;
+    pname = "kernel_abi_check";
+    hash = "sha256-goWC7SK79FVNEvkp3bISBwbOqdSrmobANtrWIve9/Ys=";
+  };
+
+  cargoDeps = rustPlatform.fetchCargoVendor {
+    inherit pname version src sourceRoot;
+    hash = "sha256-+1jdbKsDKmG+bf0NEVYMv8t7Meuge1z2cgYfbdB9q8A=";
+  };
+
+  sourceRoot = "kernel_abi_check-${version}/bindings/python";
+
+  pyproject = true;
+
+  nativeBuildInputs = with rustPlatform; [ cargoSetupHook maturinBuildHook ];
+}

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "kernels"
-version = "0.10.1.dev0"
+version = "0.10.3"
 description = "Download compute kernels"
 authors = [
   { name = "OlivierDehaene", email = "olivier@huggingface.co" },
@@ -12,7 +12,7 @@ license = { text = "Apache-2.0" }
 readme = "README.md"
 requires-python = ">= 3.9"
 dependencies = [
-  "huggingface_hub>=0.26.0,<1.0",
+  "huggingface_hub>=0.26.0,<2.0",
   "packaging>=20.0",
   "pyyaml>=6",
   "tomli>=2.0; python_version<'3.11'",
@@ -34,6 +34,7 @@ dev = [
 ]
 
 [project.optional-dependencies]
+abi-check = ["kernel-abi-check>=0.6.2,<0.7.0"]
 torch = ["torch"]
 docs = [
   "hf-doc-builder",
@@ -45,6 +46,9 @@ kernels = "kernels.cli:main"
 [project.entry-points."egg_info.writers"]
 "kernels.lock" = "kernels.lockfile:write_egg_lockfile"
 
+[tool.isort]
+profile = "black"
+line_length = 119
 
 [tool.ruff]
 exclude = [
@@ -71,4 +75,4 @@ line-length = 119
 # Ignored rules:
 # "E501" -> line length violation
 lint.ignore = ["E501"]
-lint.select = ["E", "F", "I", "W"]
+lint.select = ["E", "F", "W"]

pytest.ini

@@ -4,4 +4,6 @@ markers =
     rocm_only: marks tests that should only run on hosts with ROCm GPUs
     darwin_only: marks tests that should only run on macOS
     xpu_only: marks tests that should only run on hosts with Intel XPUs
+    npu_only: marks tests that should only run on Ascend NPUs
     token: enable tests that require a write token
+    is_staging_test: Marks tests that should only run on a staging environment

src/kernels/check.py

@@ -0,0 +1,142 @@
+import sys
+from pathlib import Path
+
+from huggingface_hub import snapshot_download
+from kernel_abi_check import (
+    BinaryFormat,
+    IncompatibleAbi3Symbol,
+    IncompatibleMacOSVersion,
+    IncompatibleManylinuxSymbol,
+    MissingMacOSVersion,
+    NonAbi3Symbol,
+    ObjectFile,
+)
+
+from kernels.utils import CACHE_DIR
+
+
+def check_kernel(
+    *, macos: str, manylinux: str, python_abi: str, repo_id: str, revision: str
+):
+    variants_path = (
+        Path(
+            snapshot_download(
+                repo_id,
+                allow_patterns=["build/*"],
+                cache_dir=CACHE_DIR,
+                revision=revision,
+            )
+        )
+        / "build"
+    )
+
+    has_issues = False
+    for variant_path in variants_path.iterdir():
+        if not variant_path.is_dir():
+            print(
+                f"⛔ `build/` must only contain directories, found: {variant_path.name}",
+                file=sys.stderr,
+            )
+            has_issues = True
+            continue
+
+        print(f"Checking variant: {variant_path.name}", file=sys.stderr)
+
+        indent = 2
+
+        for dylib_path in variant_path.rglob("*.so"):
+            print_with_indent(
+                indent,
+                f"Dynamic library {dylib_path.relative_to(variant_path)}:",
+            )
+
+            o = ObjectFile(dylib_path)
+            has_issues |= check_abi3(o, python_abi, indent + 2)
+
+            # TODO: also check operating system
+            if o.format() == BinaryFormat.ELF:
+                has_issues |= check_manylinux(o, manylinux, indent + 2)
+            elif o.format() == BinaryFormat.MACH_O:
+                has_issues |= check_macos(o, macos, indent + 2)
+
+    if has_issues:
+        sys.exit(1)
+
+
+def check_abi3(object_file: ObjectFile, python_abi: str, indent: int) -> bool:
+    has_issues = False
+    violations = object_file.check_python_abi(python_abi)
+    if violations != []:
+        has_issues = True
+        print_with_indent(
+            indent,
+            f"⛔ Found symbols that are incompatible with Python ABI {python_abi}:",
+        )
+        for violation in violations:
+            if isinstance(violation, IncompatibleAbi3Symbol):
+                print_with_indent(
+                    indent + 3,
+                    f"{violation.name}: {violation.version_added}",
+                )
+            elif isinstance(violation, NonAbi3Symbol):
+                print_with_indent(
+                    indent + 3,
+                    f"{violation.name}",
+                )
+    else:
+        print_with_indent(indent, f"🐍 Python ABI {python_abi} compatible")
+
+    return has_issues
+
+
+def check_macos(object_file: ObjectFile, macos: str, indent: int) -> bool:
+    has_issues = False
+    violations = object_file.check_macos(macos)
+    if violations != []:
+        has_issues = True
+        print_with_indent(
+            indent,
+            f"⛔ Found incompatibility with macOS {macos}:",
+        )
+
+        for violation in violations:
+            if isinstance(violation, MissingMacOSVersion):
+                print_with_indent(
+                    indent + 3,
+                    "shared library does not contain macOS version",
+                )
+            elif isinstance(violation, IncompatibleMacOSVersion):
+                print_with_indent(
+                    indent + 3,
+                    f"shared library requires macOS {violation.version}",
+                )
+    else:
+        print_with_indent(indent, f"🍏 compatible with macOS {macos}")
+
+    return has_issues
+
+
+def check_manylinux(object_file: ObjectFile, manylinux: str, indent: int) -> bool:
+    has_issues = False
+    violations = object_file.check_manylinux(manylinux)
+    if violations != []:
+        has_issues = True
+        print_with_indent(
+            indent,
+            f"⛔ Found symbols that are incompatible with {manylinux}:",
+        )
+
+        for violation in violations:
+            if isinstance(violation, IncompatibleManylinuxSymbol):
+                print_with_indent(
+                    indent + 3,
+                    f"{violation.name}_{violation.dep}: {violation.version}",
+                )
+    else:
+        print_with_indent(indent, f"🐧 {manylinux} compatible")
+
+    return has_issues
+
+
+def print_with_indent(indent: int, message: str):
+    print(f"{' ' * indent}{message}", file=sys.stderr)

src/kernels/cli.py

@@ -20,6 +20,31 @@ def main():
     )
     subparsers = parser.add_subparsers(required=True)
 
+    check_parser = subparsers.add_parser("check", help="Check a kernel for compliance")
+    check_parser.add_argument("repo_id", type=str, help="The kernel repo ID")
+    check_parser.add_argument(
+        "--revision",
+        type=str,
+        default="main",
+        help="The kernel revision (branch, tag, or commit SHA, defaults to 'main')",
+    )
+    check_parser.add_argument("--macos", type=str, help="macOS version", default="15.0")
+    check_parser.add_argument(
+        "--manylinux", type=str, help="Manylinux version", default="manylinux_2_28"
+    )
+    check_parser.add_argument(
+        "--python-abi", type=str, help="Python ABI version", default="3.9"
+    )
+    check_parser.set_defaults(
+        func=lambda args: check_kernel(
+            macos=args.macos,
+            manylinux=args.manylinux,
+            python_abi=args.python_abi,
+            repo_id=args.repo_id,
+            revision=args.revision,
+        )
+    )
+
     download_parser = subparsers.add_parser("download", help="Download locked kernels")
     download_parser.add_argument(
         "project_dir",
@@ -44,6 +69,11 @@ def main():
         type=str,
         help="Repository ID to use to upload to the Hugging Face Hub",
     )
+    upload_parser.add_argument(
+        "--branch",
+        type=None,
+        help="If set, the upload will be made to a particular branch of the provided `repo_id`.",
+    )
     upload_parser.add_argument(
         "--private",
         action="store_true",
@@ -193,6 +223,7 @@ def upload_kernels(args):
     upload_folder(
         repo_id=repo_id,
         folder_path=build_dir,
+        revision=args.branch,
         path_in_repo="build",
         delete_patterns=list(delete_patterns),
         commit_message="Build uploaded using `kernels`.",
@@ -205,3 +236,24 @@ class _JSONEncoder(json.JSONEncoder):
         if dataclasses.is_dataclass(o):
             return dataclasses.asdict(o)
         return super().default(o)
+
+
+def check_kernel(
+    *, macos: str, manylinux: str, python_abi: str, repo_id: str, revision: str
+):
+    try:
+        import kernels.check
+    except ImportError:
+        print(
+            "`kernels check` requires the `kernel-abi-check` package: pip install kernel-abi-check",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
+    kernels.check.check_kernel(
+        macos=macos,
+        manylinux=manylinux,
+        python_abi=python_abi,
+        repo_id=repo_id,
+        revision=revision,
+    )

src/kernels/layer.py

@@ -87,7 +87,7 @@ class Device:
 
     Args:
         type (`str`):
-            The device type (e.g., "cuda", "mps", "rocm", "xpu").
+            The device type (e.g., "cuda", "mps", "npu", "rocm", "xpu").
         properties ([`CUDAProperties`], *optional*):
             Device-specific properties. Currently only [`CUDAProperties`] is supported for CUDA devices.
 
@@ -109,6 +109,9 @@ class Device:
 
         # XPU device (e.g., Intel(R) Data Center GPU Max 1550)
         xpu_device = Device(type="xpu")
+
+        # NPU device (Huawei Ascend)
+        npu_device = Device(type="npu")
         ```
     """
 
@@ -130,6 +133,8 @@ class Device:
             return _MPSRepos()
         elif self.type == "xpu":
             return _XPURepos()
+        elif self.type == "npu":
+            return _NPURepos()
         else:
             raise ValueError(f"Unknown device type: {self.type}")
 
@@ -472,6 +477,26 @@ class _XPURepos(_DeviceRepos):
         self._repos = repos
 
 
+class _NPURepos(_DeviceRepos):
+    _repos: Dict[Mode, LayerRepositoryProtocol]
+
+    def __init__(self):
+        super().__init__()
+        self._repos = {}
+
+    @property
+    def repos(
+        self,
+    ) -> Optional[Dict[Mode, LayerRepositoryProtocol]]:
+        return self._repos
+
+    def insert(self, device: Device, repos: Dict[Mode, LayerRepositoryProtocol]):
+        if device.type != "npu":
+            raise ValueError(f"Device type must be 'npu', got {device.type}")
+
+        self._repos = repos
+
+
 class _MPSRepos(_DeviceRepos):
     _repos: Dict[Mode, LayerRepositoryProtocol]
 
@@ -556,7 +581,7 @@ class _ROCMRepos(_DeviceRepos):
 
 def _validate_device_type(device_type: str) -> None:
     """Validate that the device type is supported."""
-    supported_devices = {"cuda", "rocm", "mps", "xpu"}
+    supported_devices = {"cuda", "mps", "npu", "rocm", "xpu"}
     if device_type not in supported_devices:
         raise ValueError(
             f"Unsupported device type '{device_type}'. Supported device types are: {', '.join(sorted(supported_devices))}"
@@ -814,7 +839,7 @@ def kernelize(
             `Mode.TRAINING | Mode.TORCH_COMPILE` kernelizes the model for training with
             `torch.compile`.
         device (`Union[str, torch.device]`, *optional*):
-            The device type to load kernels for. Supported device types are: "cuda", "mps", "rocm", "xpu".
+            The device type to load kernels for. Supported device types are: "cuda", "mps", "npu", "rocm", "xpu".
             The device type will be inferred from the model parameters when not provided.
         use_fallback (`bool`, *optional*, defaults to `True`):
             Whether to use the original forward method of modules when no compatible kernel could be found.
@@ -838,7 +863,7 @@ def kernelize(
                 return F.silu(x[..., :d]) * x[..., d:]
 
         mapping = {
-            "LayerNorm": {
+            "SiluAndMul": {
                 "cuda": LayerRepository(
                     repo_id="kernels-community/activation",
                     layer_name="SiluAndMul",

src/kernels/utils.py

@@ -35,6 +35,14 @@ def _get_cache_dir() -> Optional[str]:
 CACHE_DIR: Optional[str] = _get_cache_dir()
 
 
+def _get_privateuse_backend_name() -> Optional[str]:
+    import torch
+
+    if hasattr(torch._C, "_get_privateuse1_backend_name"):
+        return torch._C._get_privateuse1_backend_name()
+    return None
+
+
 def build_variant() -> str:
     import torch
 
@@ -49,9 +57,14 @@ def build_variant() -> str:
     elif torch.version.xpu is not None:
         version = torch.version.xpu
         compute_framework = f"xpu{version[0:4]}{version[5:6]}"
+    elif _get_privateuse_backend_name() == "npu":
+        from torch_npu.utils.collect_env import get_cann_version  # type: ignore[import-not-found]
+
+        cann_major, cann_minor = get_cann_version()[0], get_cann_version()[2]
+        compute_framework = f"cann{cann_major}{cann_minor}"
     else:
         raise AssertionError(
-            "Torch was not compiled with CUDA, Metal, XPU, or ROCm enabled."
+            "Torch was not compiled with CUDA, Metal, XPU, NPU, or ROCm enabled."
         )
 
     torch_version = parse(torch.__version__)

tests/conftest.py

@@ -3,6 +3,8 @@ import sys
 import pytest
 import torch
 
+from kernels.utils import _get_privateuse_backend_name
+
 has_cuda = (
     hasattr(torch.version, "cuda")
     and torch.version.cuda is not None
@@ -18,6 +20,7 @@ has_xpu = (
     and torch.version.xpu is not None
     and torch.xpu.device_count() > 0
 )
+has_npu = _get_privateuse_backend_name() == "npu"
 
 
 def pytest_addoption(parser):
@@ -37,5 +40,7 @@ def pytest_runtest_setup(item):
         pytest.skip("skipping macOS-only test on non-macOS platform")
     if "xpu_only" in item.keywords and not has_xpu:
         pytest.skip("skipping XPU-only test on host without XPU")
+    if "npu_only" in item.keywords and not has_npu:
+        pytest.skip("skipping NPU-only test on host without NPU")
     if "token" in item.keywords and not item.config.getoption("--token"):
         pytest.skip("need --token option to run this test")

tests/kernel_locking/kernels.lock

@@ -1,82 +1,70 @@
 [
   {
     "repo_id": "kernels-community/activation",
-    "sha": "fd6842e88f1f23f198551d78a4541b8eb07e0538",
+    "sha": "83046852be158d525114f68513cd79fd88911b37",
     "variants": {
-      "torch25-cxx11-cu118-x86_64-linux": {
-        "hash": "sha256-61e3e51b5b59b30d4a6ba943a5e6e4ef5a9c8260cc4bca40b9fb462c0777842b",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch25-cxx11-cu121-x86_64-linux": {
-        "hash": "sha256-baa6b872040730bd1d676c011381f6f626fb96189837b828f587c806af8994fa",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch25-cxx11-cu124-x86_64-linux": {
-        "hash": "sha256-c1ec7457847fa1f0e4ab43234dfc3cd0959977e03dc2ffe89b4f6b90970c7965",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch25-cxx98-cu118-x86_64-linux": {
-        "hash": "sha256-412f9c841f20741e42f2c6cdb8c7da0e33ab436b219975acffe18b62b97ecd7c",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch25-cxx98-cu121-x86_64-linux": {
-        "hash": "sha256-2fde7f97859506e000c1072b3916c0a75bc8cee750a9853ea8b68199e7b57bcd",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch25-cxx98-cu124-x86_64-linux": {
-        "hash": "sha256-93309986f39a64a5630378108154866f0545178fa8dfef9b8f8ccfef9a78608e",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx11-cu118-x86_64-linux": {
-        "hash": "sha256-3284d3c64b76d92c1ee930bce8013aff307f16eefb16c2d5dea9f2ca70e71e1f",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx11-cu124-x86_64-linux": {
-        "hash": "sha256-36a8c93773c08ddf8ef624a8a6b2866be26d1861450dfe1ecac0bed59f9ffa47",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx11-cu126-aarch64-linux": {
-        "hash": "sha256-f5afb734520f587717665659798ff738a69e5ae1e34d4bd95624edd18fb165cd",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx11-cu126-x86_64-linux": {
-        "hash": "sha256-940841a7cb44f76c9a896d8b39f5bc0e0420f1c4c05ae9423da96778de4d1f2c",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx98-cu118-x86_64-linux": {
-        "hash": "sha256-8e0f907830c3acc8c6bebfc162c744012ff6973e8110d7bf8ecd74b492418204",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx98-cu124-x86_64-linux": {
-        "hash": "sha256-0833414cbe658baec55b7ff63537cddccc973fe99e3c03008cced5e66e38b6c1",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx98-cu126-aarch64-linux": {
-        "hash": "sha256-d94fa59a13a5b623b2071aadcd1e6c8477c4d557fd06ad144f15b46b1fc71aab",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch26-cxx98-cu126-x86_64-linux": {
-        "hash": "sha256-64784f5f2f9e232d0f2fd824fbc47eadde505e3c232f351bead5b04c429c65c2",
-        "hash_type": "git_lfs_concat"
-      },
       "torch27-cxx11-cu118-x86_64-linux": {
-        "hash": "sha256-bcba3765f061649bac0e5a9159bea8349ced4780e24a2330aa62ce0f8d3a9d78",
-        "hash_type": "git_lfs_concat"
-      },
-      "torch27-cxx11-cu126-aarch64-linux": {
-        "hash": "sha256-e4625df5706af025c70bd824d952b928d9a2965eeaefda72fc47be0fae680c5e",
+        "hash": "sha256-e34965c814c4c092fcb634ebadefe82ea9a05b98343f8ebdefa7305dcc05359e",
         "hash_type": "git_lfs_concat"
       },
       "torch27-cxx11-cu126-x86_64-linux": {
-        "hash": "sha256-7d7d3e655f34a7b03d5603d7c1ab723ef3efc823291762421a8b3a4aa51bd405",
+        "hash": "sha256-5f92b35922b37224a416398a39a29b7e5f1aca1df17d5c69f1b9e9cdb7033561",
         "hash_type": "git_lfs_concat"
       },
       "torch27-cxx11-cu128-aarch64-linux": {
-        "hash": "sha256-60e076194dcd55b32c5aca72f09816cba0fff52f340c8a063b17ff0577154d99",
+        "hash": "sha256-125967cb23bacd2cec443799f184ac08247dfff33f5027e54ee16d3779ca5986",
         "hash_type": "git_lfs_concat"
       },
       "torch27-cxx11-cu128-x86_64-linux": {
-        "hash": "sha256-f0a3802382efdcd78b40601187a9c416579a24ef2ed5a60d2296ef0951a89597",
+        "hash": "sha256-496a84c99d7035a1b6f0ea1c026b751c3a2677956f4c1be546d3cc1505a5fdbb",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu126-aarch64-linux": {
+        "hash": "sha256-f0775a30ffa290c90aba3a41037e3ca91edb15b4a9367561fafd5f25455e117a",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu126-x86_64-linux": {
+        "hash": "sha256-081995e6230f306bdf6111186618794f2411cf0ffd9b4800330df60b4ebe1927",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu128-aarch64-linux": {
+        "hash": "sha256-b937fef62a0c1cd71ab98490b651c473577af209b9a3e2a6b452350283d8812c",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu128-x86_64-linux": {
+        "hash": "sha256-a3915686cc58641a3361ece63ab77b33e9d30315dea12547e4bda008d8810a01",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu129-aarch64-linux": {
+        "hash": "sha256-a24dca8e998f88be42491921c9df89d88a6112ca630acd2efc2dd34a64b91fcb",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch28-cxx11-cu129-x86_64-linux": {
+        "hash": "sha256-df6c70a70f425db2f68b86561c6f93c5675c1d5e5d058766d88ab17472229907",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu126-aarch64-linux": {
+        "hash": "sha256-c120011c201072b4cfd70c2ba2d45c2f05337feaf604ddec3c6c4987def33ab3",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu126-x86_64-linux": {
+        "hash": "sha256-765a7f3279009979be4001a23c5c70e5e6ab9553098d67886731a5275a6d4b32",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu128-aarch64-linux": {
+        "hash": "sha256-266d057a9cd82b872a0e02f09ac5e2660fcffcf9a7b7fa1fa8ff33dc19c0f5c2",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu128-x86_64-linux": {
+        "hash": "sha256-6850e594ba4588f289b5904eb88eda5a41870ee20a3bf1586f3268307caf4b53",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu130-aarch64-linux": {
+        "hash": "sha256-23741b935462b53bdf868f8d1c9c8cff5f02f71ea3b0550df41dc8b030b0b474",
+        "hash_type": "git_lfs_concat"
+      },
+      "torch29-cxx11-cu130-x86_64-linux": {
+        "hash": "sha256-b884ae792dc1eada071f31645add0c2c76d479864f25aebcdd8318b675aaaf29",
         "hash_type": "git_lfs_concat"
       }
     }

tests/test_kernel_locking.py

@@ -35,6 +35,7 @@ def test_load_locked():
     load_kernel("kernels-community/activation", lockfile=project_dir / "kernels.lock")
 
 
+@pytest.mark.cuda_only
 def test_layer_locked():
     project_dir = Path(__file__).parent / "layer_locking"
 

tests/test_kernel_upload.py

@@ -7,11 +7,12 @@ from pathlib import Path
 from typing import List
 
 import pytest
-from huggingface_hub import model_info
+from huggingface_hub import delete_repo, model_info
 
 from kernels.cli import upload_kernels
 
-REPO_ID = "kernels-test/kernels-upload-test"
+REPO_ID = "valid_org/kernels-upload-test"
+
 
 PY_CONTENT = """\
 #!/usr/bin/env python3
@@ -29,6 +30,7 @@ class UploadArgs:
     kernel_dir: None
     repo_id: None
     private: False
+    branch: None
 
 
 def next_filename(path: Path) -> Path:
@@ -68,7 +70,33 @@ def get_filenames_from_a_repo(repo_id: str) -> List[str]:
 
 
 @pytest.mark.token
+@pytest.mark.is_staging_test
+@pytest.mark.parametrize("branch", (None, "foo"))
+def test_kernel_upload_works_as_expected(branch):
+    with tempfile.TemporaryDirectory() as tmpdir:
+        path = f"{tmpdir}/build/torch-universal/upload_test"
+        build_dir = Path(path)
+        build_dir.mkdir(parents=True, exist_ok=True)
+        script_path = build_dir / "foo.py"
+        script_path.write_text(PY_CONTENT)
+        upload_kernels(UploadArgs(tmpdir, REPO_ID, False, branch))
+
+    repo_filenames = get_filenames_from_a_repo(REPO_ID)
+    assert any(str(script_path.name) for f in repo_filenames)
+    delete_repo(repo_id=REPO_ID)
+
+
+@pytest.mark.token
+@pytest.mark.is_staging_test
 def test_kernel_upload_deletes_as_expected():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        path = f"{tmpdir}/build/torch-universal/upload_test"
+        build_dir = Path(path)
+        build_dir.mkdir(parents=True, exist_ok=True)
+        script_path = build_dir / "foo_2025.py"
+        script_path.write_text(PY_CONTENT)
+        upload_kernels(UploadArgs(tmpdir, REPO_ID, False))
+
     repo_filenames = get_filenames_from_a_repo(REPO_ID)
     filename_to_change = get_filename_to_change(repo_filenames)
 
@@ -86,3 +114,4 @@ def test_kernel_upload_deletes_as_expected():
     assert not any(
         str(filename_to_change) in k for k in repo_filenames
     ), f"{repo_filenames=}"
+    delete_repo(repo_id=REPO_ID)

tests/test_layer.py

@@ -21,14 +21,21 @@ from kernels.layer import (
     _KERNEL_MAPPING,
     _validate_layer,
 )
-from kernels.utils import install_kernel
+from kernels.utils import (
+    _get_privateuse_backend_name,
+    install_kernel,
+)
 
 kernel_layer_mapping = {
     "SiluAndMul": {
         Device(type="cuda"): LayerRepository(
             repo_id="kernels-community/activation",
             layer_name="SiluAndMul",
-        )
+        ),
+        "npu": LayerRepository(
+            repo_id="kernels-ext-npu/SwiGlu",
+            layer_name="SwiGlu",
+        ),
     },
     "SiluAndMulNoCompile": {
         "cuda": LayerRepository(
@@ -122,8 +129,10 @@ def device():
         return "cuda"
     elif hasattr(torch, "xpu") and torch.xpu.is_available():
         return "xpu"
+    elif _get_privateuse_backend_name() == "npu":
+        return "npu"
 
-    pytest.skip("No CUDA or XPU")
+    pytest.skip("No CUDA, NPU or XPU")
 
 
 def test_arg_kinds():
@@ -204,10 +213,33 @@ def test_hub_forward_xpu():
     assert rms_norm_with_kernel.n_calls == 0
 
 
+@pytest.mark.npu_only
+def test_hub_forward_npu():
+    torch.manual_seed(0)
+
+    silu_and_mul = SiluAndMul()
+    X = torch.randn((32, 64), device="npu")
+    Y = silu_and_mul(X)
+
+    silu_and_mul_with_kernel = kernelize(
+        SiluAndMulWithKernel(), device="npu", mode=Mode.INFERENCE
+    )
+    Y_kernel = silu_and_mul_with_kernel(X)
+
+    torch.testing.assert_close(Y_kernel, Y)
+
+    assert silu_and_mul.n_calls == 1
+    assert silu_and_mul_with_kernel.n_calls == 0
+
+
 @pytest.mark.skipif(
     hasattr(torch, "xpu") and getattr(torch.xpu, "is_available", lambda: False)(),
     reason="Skip on xpu devices",
 )
+@pytest.mark.skipif(
+    _get_privateuse_backend_name() == "npu",
+    reason="Skip on npu devices",
+)
 def test_rocm_kernel_mapping():
     """Test that ROCm shorthand device mapping works correctly."""
     kernel_layer_mapping = {