Build uploaded using `kernels`.
Browse files- .gitattributes +1 -0
- build/torch211-cu128-x86_64-windows/__init__.py +16 -0
- build/torch211-cu128-x86_64-windows/_ops.py +9 -0
- build/torch211-cu128-x86_64-windows/_relu_cuda_e08ad6f.pyd +3 -0
- build/torch211-cu128-x86_64-windows/layers/__init__.py +11 -0
- build/torch211-cu128-x86_64-windows/metadata.json +21 -0
- build/torch211-cu128-x86_64-windows/relu/__init__.py +26 -0
.gitattributes
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@@ -347,3 +347,4 @@ build/torch211-cxx11-rocm71-x86_64-linux/_relu_rocm_918d6dc.abi3.so filter=lfs d
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build/torch211-cxx11-rocm72-x86_64-linux/_relu_rocm_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch211-cxx11-xpu20253-x86_64-linux/_relu_xpu_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch29-cxx11-cu129-x86_64-linux/_relu_cuda_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch211-cxx11-rocm72-x86_64-linux/_relu_rocm_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch211-cxx11-xpu20253-x86_64-linux/_relu_xpu_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch29-cxx11-cu129-x86_64-linux/_relu_cuda_918d6dc.abi3.so filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/_relu_cuda_e08ad6f.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/__init__.py
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from typing import Optional
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import torch
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from ._ops import ops
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from . import layers
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def relu(x: torch.Tensor, out: Optional[torch.Tensor] = None) -> torch.Tensor:
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if out is None:
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out = torch.empty_like(x)
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ops.relu(out, x)
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return out
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__all__ = ["relu", "layers"]
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build/torch211-cu128-x86_64-windows/_ops.py
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import torch
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from . import _relu_cuda_e08ad6f
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ops = torch.ops._relu_cuda_e08ad6f
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def add_op_namespace_prefix(op_name: str):
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"""
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Prefix op by namespace.
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"""
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return f"_relu_cuda_e08ad6f::{op_name}"
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build/torch211-cu128-x86_64-windows/_relu_cuda_e08ad6f.pyd
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0026652617bd14aa36f5dc3e6f970653006605ff14071af8874648f9ba8386b
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size 203776
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build/torch211-cu128-x86_64-windows/layers/__init__.py
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import torch
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import torch.nn as nn
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from .._ops import ops
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class ReLU(nn.Module):
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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out = torch.empty_like(x)
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ops.relu(out, x)
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return out
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build/torch211-cu128-x86_64-windows/metadata.json
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{
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"version": 1,
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"license": "Apache-2.0",
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"python-depends": [],
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"backend": {
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"type": "cuda",
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"archs": [
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"10.0",
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"10.1",
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"12.0+PTX",
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"7.0",
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"7.2",
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"7.5",
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"8.0",
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"8.6",
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"8.7",
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"8.9",
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"9.0"
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]
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}
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}
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build/torch211-cu128-x86_64-windows/relu/__init__.py
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import ctypes
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import importlib.util
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import sys
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from pathlib import Path
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from types import ModuleType
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def _import_from_path(file_path: Path) -> ModuleType:
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# We cannot use the module name as-is, after adding it to `sys.modules`,
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# it would also be used for other imports. So, we make a module name that
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# depends on the path for it to be unique using the hex-encoded hash of
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# the path.
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path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
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module_name = path_hash
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spec = importlib.util.spec_from_file_location(module_name, file_path)
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if spec is None:
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raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
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module = importlib.util.module_from_spec(spec)
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if module is None:
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raise ImportError(f"Cannot load module {module_name} from spec")
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sys.modules[module_name] = module
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spec.loader.exec_module(module) # type: ignore
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return module
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globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))
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