feat: update to include rev in kernel for reproducible symbols

README.md

@@ -2,9 +2,6 @@
 tags:
 - kernel
 ---
-
-![Status](https://hubwebhook.dholtz.com/shield?repo=kernels-community/activation)
-
 ## Activation
 
 Activation kernels from [vLLM](https://github.com/vllm-project/vllm/blob/main/csrc/activation_kernels.cu).

build.toml

@@ -1,18 +1,17 @@
 [general]
 name = "activation"
-universal = false
 
 [torch]
 src = [
-    "torch-ext/torch_binding.cpp",
-    "torch-ext/torch_binding.h",
+  "torch-ext/torch_binding.cpp",
+  "torch-ext/torch_binding.h"
 ]
 
 [kernel.activation]
-backend = "cuda"
-depends = ["torch"]
+cuda-capabilities = [ "7.0", "7.2", "7.5", "8.0", "8.6", "8.7", "8.9", "9.0" ]
 src = [
-    "activation/activation_kernels.cu",
-    "activation/cuda_compat.h",
-    "activation/dispatch_utils.h",
+  "activation/activation_kernels.cu",
+  "activation/cuda_compat.h",
+  "activation/dispatch_utils.h",
 ]
+depends = [ "torch" ]

build/{torch26-cxx11-cu118-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so → torch25-cxx11-cu118-x86_64-linux/activation/_activation_o63kkyjirmkf4.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b925dc27b6a9afd5b6d11e454275222c531a92f7ca27958ac81a78c580665e4d
-size 2448088
+oid sha256:d50cdabfbed1df74e921ac34ff00bca0555977b14ef8082ddae7b1f30985a494
+size 2370160

build/{torch27-cxx11-cu118-x86_64-linux → torch25-cxx11-cu118-x86_64-linux}/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_o63kkyjirmkf4
+ops = torch.ops._activation_o63kkyjirmkf4
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_o63kkyjirmkf4::{op_name}"

build/{torch27-cxx11-cu118-x86_64-linux → torch25-cxx11-cu118-x86_64-linux}/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/{torch26-cxx11-cu124-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so → torch25-cxx11-cu121-x86_64-linux/activation/_activation_vrl36m2ejer54.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cfdbe510752b57a8dc4671f744bb0a2da5b1646e0b9a19fec02f1505ba044c8c
-size 2509960
+oid sha256:2bd0709ef09c8f0c18d1dc4a36c8096c59459bece61f5f5dbea95d1e73f54d44
+size 2393264

build/{torch27-cxx11-cu126-x86_64-linux → torch25-cxx11-cu121-x86_64-linux}/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_vrl36m2ejer54
+ops = torch.ops._activation_vrl36m2ejer54
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_vrl36m2ejer54::{op_name}"

build/{torch27-cxx11-cu126-x86_64-linux → torch25-cxx11-cu121-x86_64-linux}/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/{torch26-cxx11-cu126-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so → torch25-cxx11-cu124-x86_64-linux/activation/_activation_va3moa75vw7c2.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:70e544ad6448a5576d26147f48403f3e9e593f4a2e24167dc8acb81ce3b7932e
-size 2518600
+oid sha256:8353447f64e7d2df1a6a341d9c53bced53abef267f079923ae774170d0d57c53
+size 2427936

build/{torch27-cxx11-cu128-x86_64-linux → torch25-cxx11-cu124-x86_64-linux}/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_va3moa75vw7c2
+ops = torch.ops._activation_va3moa75vw7c2
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_va3moa75vw7c2::{op_name}"

build/{torch27-cxx11-cu128-x86_64-linux → torch25-cxx11-cu124-x86_64-linux}/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch25-cxx98-cu118-x86_64-linux/activation/__init__.py

@@ -0,0 +1,52 @@
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def silu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.silu_and_mul(out, x)
+    return out
+
+
+def gelu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_and_mul(out, x)
+    return out
+
+
+def gelu_tanh_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_tanh_and_mul(out, x)
+    return out
+
+
+def fatrelu_and_mul(out: torch.Tensor, x: torch.Tensor, threshold: float = 0.0) -> None:
+    ops.fatrelu_and_mul(out, x, threshold)
+    return out
+
+
+def gelu_fast(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_fast(out, x)
+    return out
+
+
+def gelu_new(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_new(out, x)
+    return out
+
+
+def gelu_quick(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_quick(out, x)
+    return out
+
+
+__all__ = [
+    "silu_and_mul",
+    "gelu_and_mul",
+    "gelu_tanh_and_mul",
+    "fatrelu_and_mul",
+    "gelu_fast",
+    "gelu_new",
+    "gelu_quick",
+    "layers",
+]

build/{torch26-cxx98-cu118-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so → torch25-cxx98-cu118-x86_64-linux/activation/_activation_qr3gs3eckeig4.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:60fd224c33657558f03be5be57cc8d35ade23225b1abd71557b170c8a7010cd1
-size 2440576
+oid sha256:df184a6315118d787a1bd6b435cb45f1ca7828445a1f1c0e55c57645cfbba43a
+size 2362600

build/torch25-cxx98-cu118-x86_64-linux/activation/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _activation_qr3gs3eckeig4
+ops = torch.ops._activation_qr3gs3eckeig4
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_activation_qr3gs3eckeig4::{op_name}"

build/torch25-cxx98-cu118-x86_64-linux/activation/layers.py

@@ -0,0 +1,65 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class SiluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.silu_and_mul(out, x)
+        return out
+
+
+class GeluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_and_mul(out, x)
+        return out
+
+
+class GeluTanhAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_tanh_and_mul(out, x)
+        return out
+
+
+class FatreluAndMul(nn.Module):
+    def __init__(self, threshold: float = 0.0):
+        super().__init__()
+        self.threshold = threshold
+
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.fatrelu_and_mul(out, x, self.threshold)
+        return out
+
+
+class FastGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_fast(out, x)
+        return out
+
+
+class NewGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_new(out, x)
+        return out
+
+
+class QuickGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_quick(out, x)
+        return out

build/torch25-cxx98-cu121-x86_64-linux/activation/__init__.py

@@ -0,0 +1,52 @@
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def silu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.silu_and_mul(out, x)
+    return out
+
+
+def gelu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_and_mul(out, x)
+    return out
+
+
+def gelu_tanh_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_tanh_and_mul(out, x)
+    return out
+
+
+def fatrelu_and_mul(out: torch.Tensor, x: torch.Tensor, threshold: float = 0.0) -> None:
+    ops.fatrelu_and_mul(out, x, threshold)
+    return out
+
+
+def gelu_fast(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_fast(out, x)
+    return out
+
+
+def gelu_new(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_new(out, x)
+    return out
+
+
+def gelu_quick(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_quick(out, x)
+    return out
+
+
+__all__ = [
+    "silu_and_mul",
+    "gelu_and_mul",
+    "gelu_tanh_and_mul",
+    "fatrelu_and_mul",
+    "gelu_fast",
+    "gelu_new",
+    "gelu_quick",
+    "layers",
+]

build/torch25-cxx98-cu121-x86_64-linux/activation/_activation_p7gbzt25w3zg2.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ccb13cfc2e45cf483e8b9f77f1760f28b48bcf185508d51b32d45bc759c4e8bb
+size 2385440

build/torch25-cxx98-cu121-x86_64-linux/activation/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _activation_p7gbzt25w3zg2
+ops = torch.ops._activation_p7gbzt25w3zg2
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_activation_p7gbzt25w3zg2::{op_name}"

build/torch25-cxx98-cu121-x86_64-linux/activation/layers.py

@@ -0,0 +1,65 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class SiluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.silu_and_mul(out, x)
+        return out
+
+
+class GeluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_and_mul(out, x)
+        return out
+
+
+class GeluTanhAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_tanh_and_mul(out, x)
+        return out
+
+
+class FatreluAndMul(nn.Module):
+    def __init__(self, threshold: float = 0.0):
+        super().__init__()
+        self.threshold = threshold
+
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.fatrelu_and_mul(out, x, self.threshold)
+        return out
+
+
+class FastGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_fast(out, x)
+        return out
+
+
+class NewGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_new(out, x)
+        return out
+
+
+class QuickGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_quick(out, x)
+        return out

build/torch25-cxx98-cu124-x86_64-linux/activation/__init__.py

@@ -0,0 +1,52 @@
+import torch
+
+from ._ops import ops
+
+from . import layers
+
+
+def silu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.silu_and_mul(out, x)
+    return out
+
+
+def gelu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_and_mul(out, x)
+    return out
+
+
+def gelu_tanh_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_tanh_and_mul(out, x)
+    return out
+
+
+def fatrelu_and_mul(out: torch.Tensor, x: torch.Tensor, threshold: float = 0.0) -> None:
+    ops.fatrelu_and_mul(out, x, threshold)
+    return out
+
+
+def gelu_fast(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_fast(out, x)
+    return out
+
+
+def gelu_new(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_new(out, x)
+    return out
+
+
+def gelu_quick(out: torch.Tensor, x: torch.Tensor) -> None:
+    ops.gelu_quick(out, x)
+    return out
+
+
+__all__ = [
+    "silu_and_mul",
+    "gelu_and_mul",
+    "gelu_tanh_and_mul",
+    "fatrelu_and_mul",
+    "gelu_fast",
+    "gelu_new",
+    "gelu_quick",
+    "layers",
+]

build/torch25-cxx98-cu124-x86_64-linux/activation/_activation_jg7yaigtn7wco.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f8048853e8cb06e8574a9a9497800d2be438f7989d79f44dcf2e0ced38a75a9
+size 2420192

build/torch25-cxx98-cu124-x86_64-linux/activation/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _activation_jg7yaigtn7wco
+ops = torch.ops._activation_jg7yaigtn7wco
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_activation_jg7yaigtn7wco::{op_name}"

build/torch25-cxx98-cu124-x86_64-linux/activation/layers.py

@@ -0,0 +1,65 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class SiluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.silu_and_mul(out, x)
+        return out
+
+
+class GeluAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_and_mul(out, x)
+        return out
+
+
+class GeluTanhAndMul(nn.Module):
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.gelu_tanh_and_mul(out, x)
+        return out
+
+
+class FatreluAndMul(nn.Module):
+    def __init__(self, threshold: float = 0.0):
+        super().__init__()
+        self.threshold = threshold
+
+    def forward(self, x: torch.Tensor):
+        d = x.shape[-1] // 2
+        output_shape = x.shape[:-1] + (d,)
+        out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
+        ops.fatrelu_and_mul(out, x, self.threshold)
+        return out
+
+
+class FastGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_fast(out, x)
+        return out
+
+
+class NewGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_new(out, x)
+        return out
+
+
+class QuickGELU(nn.Module):
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        out = torch.empty_like(x)
+        ops.gelu_quick(out, x)
+        return out

build/torch26-cxx11-cu118-x86_64-linux/activation/_activation_ncisyrun7guwk.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cde5439e78ba0e1aaa1937d798b214b46d38cbab8e4384b93a22239fed1a4dd4
+size 2370264

build/torch26-cxx11-cu118-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_ncisyrun7guwk
+ops = torch.ops._activation_ncisyrun7guwk
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_ncisyrun7guwk::{op_name}"

build/torch26-cxx11-cu118-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch26-cxx11-cu124-x86_64-linux/activation/_activation_ochhfvlnc3vyc.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6bd20d411c51fc8729b15cab6a60c5c9185222474aa035489e1bff299d76682
+size 2428040

build/torch26-cxx11-cu124-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_ochhfvlnc3vyc
+ops = torch.ops._activation_ochhfvlnc3vyc
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_ochhfvlnc3vyc::{op_name}"

build/torch26-cxx11-cu124-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch26-cxx11-cu126-x86_64-linux/activation/_activation_u6vnqubnicksq.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:41c18b20c2bf8c49d2d3088a9bc1aad4293df0b57eafc9b141a9e8e595fe551a
+size 2436672

build/torch26-cxx11-cu126-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_u6vnqubnicksq
+ops = torch.ops._activation_u6vnqubnicksq
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_u6vnqubnicksq::{op_name}"

build/torch26-cxx11-cu126-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch26-cxx98-cu118-x86_64-linux/activation/_activation_2vn6ty3gfqfb6.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfbcd5da358cd5cb7982d19c8880cf4db6f08b46622a7a953f755ad59e4e1492
+size 2362752

build/torch26-cxx98-cu118-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_2vn6ty3gfqfb6
+ops = torch.ops._activation_2vn6ty3gfqfb6
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_2vn6ty3gfqfb6::{op_name}"

build/torch26-cxx98-cu118-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch26-cxx98-cu124-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e364773259dc1b91f3c0d3b076da83c5a9c6ee18ffdace30315c602dffd1dabe
-size 2502264

build/torch26-cxx98-cu124-x86_64-linux/activation/_activation_myvteedxdpqc6.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b1bc928823117c800904bcd3492bf1a0c65a32f6d8a842dc039f55e29831ab49
+size 2420344

build/torch26-cxx98-cu124-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_myvteedxdpqc6
+ops = torch.ops._activation_myvteedxdpqc6
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_myvteedxdpqc6::{op_name}"

build/torch26-cxx98-cu124-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch26-cxx98-cu126-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7ac88cc0d3c65ab283d20608f3a097be29ee572e7856f10f8d7919536efd95b4
-size 2506808

build/torch26-cxx98-cu126-x86_64-linux/activation/_activation_rbswus6emrhm2.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:474727e434a9cd4ec984a6da7124992ead4ca0fefce9581d0fd503e36c065aed
+size 2424888

build/torch26-cxx98-cu126-x86_64-linux/activation/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _activation_e99cc09_dirty
-ops = torch.ops._activation_e99cc09_dirty
+from . import _activation_rbswus6emrhm2
+ops = torch.ops._activation_rbswus6emrhm2
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_activation_e99cc09_dirty::{op_name}"
+    return f"_activation_rbswus6emrhm2::{op_name}"

build/torch26-cxx98-cu126-x86_64-linux/activation/layers.py

@@ -5,8 +5,6 @@ from ._ops import ops
 
 
 class SiluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -16,8 +14,6 @@ class SiluAndMul(nn.Module):
 
 
 class GeluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -27,8 +23,6 @@ class GeluAndMul(nn.Module):
 
 
 class GeluTanhAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor):
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
@@ -38,8 +32,6 @@ class GeluTanhAndMul(nn.Module):
 
 
 class FatreluAndMul(nn.Module):
-    can_torch_compile: bool = True
-
     def __init__(self, threshold: float = 0.0):
         super().__init__()
         self.threshold = threshold
@@ -53,8 +45,6 @@ class FatreluAndMul(nn.Module):
 
 
 class FastGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_fast(out, x)
@@ -62,8 +52,6 @@ class FastGELU(nn.Module):
 
 
 class NewGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_new(out, x)
@@ -71,8 +59,6 @@ class NewGELU(nn.Module):
 
 
 class QuickGELU(nn.Module):
-    can_torch_compile: bool = True
-
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         out = torch.empty_like(x)
         ops.gelu_quick(out, x)

build/torch27-cxx11-cu118-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e4f9e647eea40d3d3801d5ee57d4917e4c2e8dbfd87cdfebdc40b1b0a1c571fe
-size 2448184

build/torch27-cxx11-cu126-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a2b72ff2a0f2253e4dfe028842b5f15cabf2647d7812bf4662a2de510ca0c489
-size 2518632

build/torch27-cxx11-cu128-x86_64-linux/activation/_activation_e99cc09_dirty.abi3.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f4590c852899e4c11ddb74cfad61e26b07490a91f3c09e0fb0874a3fcc1f533e
-size 3331456

flake.lock

@@ -1,168 +0,0 @@
-{
-  "nodes": {
-    "flake-compat": {
-      "locked": {
-        "lastModified": 1747046372,
-        "narHash": "sha256-CIVLLkVgvHYbgI2UpXvIIBJ12HWgX+fjA8Xf8PUmqCY=",
-        "owner": "edolstra",
-        "repo": "flake-compat",
-        "rev": "9100a0f413b0c601e0533d1d94ffd501ce2e7885",
-        "type": "github"
-      },
-      "original": {
-        "owner": "edolstra",
-        "repo": "flake-compat",
-        "type": "github"
-      }
-    },
-    "flake-compat_2": {
-      "locked": {
-        "lastModified": 1733328505,
-        "narHash": "sha256-NeCCThCEP3eCl2l/+27kNNK7QrwZB1IJCrXfrbv5oqU=",
-        "owner": "edolstra",
-        "repo": "flake-compat",
-        "rev": "ff81ac966bb2cae68946d5ed5fc4994f96d0ffec",
-        "type": "github"
-      },
-      "original": {
-        "owner": "edolstra",
-        "repo": "flake-compat",
-        "type": "github"
-      }
-    },
-    "flake-utils": {
-      "inputs": {
-        "systems": "systems"
-      },
-      "locked": {
-        "lastModified": 1731533236,
-        "narHash": "sha256-l0KFg5HjrsfsO/JpG+r7fRrqm12kzFHyUHqHCVpMMbI=",
-        "owner": "numtide",
-        "repo": "flake-utils",
-        "rev": "11707dc2f618dd54ca8739b309ec4fc024de578b",
-        "type": "github"
-      },
-      "original": {
-        "owner": "numtide",
-        "repo": "flake-utils",
-        "type": "github"
-      }
-    },
-    "flake-utils_2": {
-      "inputs": {
-        "systems": "systems_2"
-      },
-      "locked": {
-        "lastModified": 1731533236,
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