Build uploaded using `kernels`.

.gitattributes

@@ -250,3 +250,11 @@ build/torch210-xpu20253-x86_64-windows/_relu_xpu_bd0179a.pyd filter=lfs diff=lfs
 build/torch210-cu128-x86_64-windows/_relu_cuda_d91a431.pyd filter=lfs diff=lfs merge=lfs -text
 build/torch210-xpu20253-x86_64-windows/_relu_xpu_d91a431.pyd filter=lfs diff=lfs merge=lfs -text
 build/torch210-metal-aarch64-darwin/_relu_metal_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cpu-aarch64-linux/_relu_cpu_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu126-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu128-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu130-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cpu-aarch64-linux/_relu_cpu_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu126-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu128-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu130-aarch64-linux/_relu_cuda_6261c06.abi3.so filter=lfs diff=lfs merge=lfs -text

build/torch210-cxx11-cpu-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch210-cxx11-cpu-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cpu_6261c06
+ops = torch.ops._relu_cpu_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cpu_6261c06::{op_name}"

build/torch210-cxx11-cpu-aarch64-linux/_relu_cpu_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4a447fd999d3560323e510da358696da51c23ba3eef87e1fb8b57683a2a8f68
+size 2025352

build/torch210-cxx11-cpu-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch210-cxx11-cpu-aarch64-linux/metadata.json

@@ -0,0 +1,5 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": []
+}

build/torch210-cxx11-cpu-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu126-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch210-cxx11-cu126-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch210-cxx11-cu126-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f55e81ff893a372fe86ad6443371abe2eb30ee2dc9e8d16ce7cc32309adc21d
+size 2103912

build/torch210-cxx11-cu126-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch210-cxx11-cu126-aarch64-linux/metadata.json

@@ -0,0 +1,18 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  }
+}

build/torch210-cxx11-cu126-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu128-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch210-cxx11-cu128-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch210-cxx11-cu128-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dbb4280ecde7decc222502fc79ed7dce04a1a3a4c6ba410140898d549cc475fd
+size 2235240

build/torch210-cxx11-cu128-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch210-cxx11-cu128-aarch64-linux/metadata.json

@@ -0,0 +1,21 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}

build/torch210-cxx11-cu128-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu130-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch210-cxx11-cu130-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch210-cxx11-cu130-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c6ce11cdbee562207b55c3bab5faeaf98c7e1fa87bcdcef231ccbd8005bb561
+size 2236952

build/torch210-cxx11-cu130-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch210-cxx11-cu130-aarch64-linux/metadata.json

@@ -0,0 +1,19 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "11.0",
+      "12.0+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}

build/torch210-cxx11-cu130-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cpu-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch29-cxx11-cpu-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cpu_6261c06
+ops = torch.ops._relu_cpu_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cpu_6261c06::{op_name}"

build/torch29-cxx11-cpu-aarch64-linux/_relu_cpu_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e4a69b4b60cdde8c27497aa5dc37ba4ee0e736b833c34ae84a2da09cb869090e
+size 2024136

build/torch29-cxx11-cpu-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch29-cxx11-cpu-aarch64-linux/metadata.json

@@ -0,0 +1,5 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": []
+}

build/torch29-cxx11-cpu-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cu126-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch29-cxx11-cu126-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch29-cxx11-cu126-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0da6a76fa50ddd780d807f638a7b122d4e21ec41383e977621a8e675921efe39
+size 2101784

build/torch29-cxx11-cu126-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch29-cxx11-cu126-aarch64-linux/metadata.json

@@ -0,0 +1,18 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  }
+}

build/torch29-cxx11-cu126-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cu128-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch29-cxx11-cu128-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch29-cxx11-cu128-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f16d75e275c8d0cf86c119e8e7acdf0ed35a97f6d14097808f0a6407d56a9246
+size 2232968

build/torch29-cxx11-cu128-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch29-cxx11-cu128-aarch64-linux/metadata.json

@@ -0,0 +1,21 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}

build/torch29-cxx11-cu128-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cu130-aarch64-linux/__init__.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
+    if out is None:
+        out = torch.empty_like(x)
+    ops.relu(out, x)
+    return out
+
+__all__ = ["relu", "layers"]

build/torch29-cxx11-cu130-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cuda_6261c06
+ops = torch.ops._relu_cuda_6261c06
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cuda_6261c06::{op_name}"

build/torch29-cxx11-cu130-aarch64-linux/_relu_cuda_6261c06.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c59120f175cd03135e9ef7058f0293d500d0e43585a0965857e6b4be9d6f90fb
+size 2234680

build/torch29-cxx11-cu130-aarch64-linux/layers/__init__.py

@@ -0,0 +1,11 @@
+import torch
+import torch.nn as nn
+
+from .._ops import ops
+
+
+class ReLU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.relu(out, x)
+        return out

build/torch29-cxx11-cu130-aarch64-linux/metadata.json

@@ -0,0 +1,19 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "11.0",
+      "12.0+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}

build/torch29-cxx11-cu130-aarch64-linux/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))