Build uploaded using `kernels`.

.gitattributes

@@ -211,3 +211,4 @@ build/torch29-cxx11-rocm63-x86_64-linux/_relu_ff7d195.abi3.so filter=lfs diff=lf
 build/torch29-cxx11-rocm64-x86_64-linux/_relu_ff7d195.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch29-cxx11-xpu20252-x86_64-linux/_relu_ff7d195.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch210-xpu20253-x86_64-windows/relu/_relu_d7b860a.pyd filter=lfs diff=lfs merge=lfs -text
+build/torch210-metal-aarch64-darwin/_relu_2b7ea88.abi3.so filter=lfs diff=lfs merge=lfs -text

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

@@ -0,0 +1,12 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+
+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

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

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_2b7ea88
+ops = torch.ops._relu_2b7ea88
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_2b7ea88::{op_name}"

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

@@ -0,0 +1,4 @@
+{
+  "version": 1,
+  "python-depends": []
+}

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

@@ -1,9 +1,9 @@
 import torch
-from . import _relu_ff7d195
-ops = torch.ops._relu_ff7d195
+from . import _relu_2b7ea88
+ops = torch.ops._relu_2b7ea88
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_relu_ff7d195::{op_name}"
+    return f"_relu_2b7ea88::{op_name}"

build/torch210-metal-aarch64-darwin/{_relu_ff7d195.abi3.so → _relu_2b7ea88.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f7043c3a657f31236f1d9e055008a6c683ab96be79aeabc800a363233d507f77
+oid sha256:e329f8b116d8f0e04ba517bf47055742b1a7ba8505df3c1960d93d873006c0bd
 size 100632

build/torch29-cpu-aarch64-darwin/__init__.py

@@ -0,0 +1,12 @@
+from typing import Optional
+
+import torch
+
+from ._ops import ops
+
+
+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

build/torch29-cpu-aarch64-darwin/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _relu_2b7ea88
+ops = torch.ops._relu_2b7ea88
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_relu_2b7ea88::{op_name}"

build/torch29-cpu-aarch64-darwin/metadata.json

@@ -0,0 +1,4 @@
+{
+  "version": 1,
+  "python-depends": []
+}

build/torch29-cpu-aarch64-darwin/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-metal-aarch64-darwin/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _relu_ff7d195
-ops = torch.ops._relu_ff7d195
+from . import _relu_2b7ea88
+ops = torch.ops._relu_2b7ea88
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_relu_ff7d195::{op_name}"
+    return f"_relu_2b7ea88::{op_name}"