Uploaded using `kernel-builder`.

.gitattributes

@@ -362,3 +362,5 @@ build/torch211-cu128-x86_64-windows/_relu_cuda_f560032.pyd filter=lfs diff=lfs m
 build/torch210-xpu20253-x86_64-windows/_relu_xpu_f560032.pyd filter=lfs diff=lfs merge=lfs -text
 build/torch211-cu128-x86_64-windows/_relu_cuda_e46713e.pyd filter=lfs diff=lfs merge=lfs -text
 build/torch210-xpu20253-x86_64-windows/_relu_xpu_e46713e.pyd filter=lfs diff=lfs merge=lfs -text
+build/torch210-metal-aarch64-darwin/_relu_metal_a99dbbb.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch211-metal-aarch64-darwin/_relu_metal_a99dbbb.abi3.so filter=lfs diff=lfs merge=lfs -text

build/torch210-cpu-aarch64-darwin/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _relu_cpu_6261c06
-ops = torch.ops._relu_cpu_6261c06
+from . import _relu_cpu_a99dbbb
+ops = torch.ops._relu_cpu_a99dbbb
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_relu_cpu_6261c06::{op_name}"
+    return f"_relu_cpu_a99dbbb::{op_name}"

build/torch210-cpu-aarch64-darwin/metadata.json

@@ -1,5 +1,8 @@
 {
   "version": 1,
   "license": "Apache-2.0",
-  "python-depends": []
+  "python-depends": [],
+  "backend": {
+    "type": "cpu"
+  }
 }

build/torch210-cpu-aarch64-darwin/relu/__init__.py

@@ -1,10 +1,10 @@
 import ctypes
+import importlib.util
 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

build/torch210-metal-aarch64-darwin/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _relu_metal_6261c06
-ops = torch.ops._relu_metal_6261c06
+from . import _relu_metal_a99dbbb
+ops = torch.ops._relu_metal_a99dbbb
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_relu_metal_6261c06::{op_name}"
+    return f"_relu_metal_a99dbbb::{op_name}"

build/torch210-metal-aarch64-darwin/{_relu_metal_6261c06.abi3.so → _relu_metal_a99dbbb.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8dfb5099b945261311ae3e457b78b0acd63463c84f73246c2492d19698cfaaae
-size 100680
+oid sha256:48ad903b6d767d68b32bad56cdae3f7e845e211680c3c49d5aafc12b4f604f70
+size 100920

build/torch210-metal-aarch64-darwin/metadata.json

@@ -1,5 +1,8 @@
 {
   "version": 1,
   "license": "Apache-2.0",
-  "python-depends": []
+  "python-depends": [],
+  "backend": {
+    "type": "metal"
+  }
 }

build/torch210-metal-aarch64-darwin/relu/__init__.py

@@ -1,10 +1,10 @@
 import ctypes
+import importlib.util
 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

build/torch211-cpu-aarch64-darwin/__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/torch211-cpu-aarch64-darwin/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_cpu_a99dbbb
+ops = torch.ops._relu_cpu_a99dbbb
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_cpu_a99dbbb::{op_name}"

build/torch211-cpu-aarch64-darwin/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/torch211-cpu-aarch64-darwin/metadata.json

@@ -0,0 +1,8 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "cpu"
+  }
+}

build/torch211-cpu-aarch64-darwin/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import importlib.util
+import sys
+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/torch211-metal-aarch64-darwin/__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/torch211-metal-aarch64-darwin/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_metal_a99dbbb
+ops = torch.ops._relu_metal_a99dbbb
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_metal_a99dbbb::{op_name}"

build/torch211-metal-aarch64-darwin/_relu_metal_a99dbbb.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a50fc4ae8185050cfacb50657bfb0a83c0efd188dd800dd02ce804f7f5be66d7
+size 100920

build/torch211-metal-aarch64-darwin/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/torch211-metal-aarch64-darwin/metadata.json

@@ -0,0 +1,8 @@
+{
+  "version": 1,
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "backend": {
+    "type": "metal"
+  }
+}

build/torch211-metal-aarch64-darwin/relu/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import importlib.util
+import sys
+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")))