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kernels-bot commited on 11 days ago

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build/torch210-cpu-x86_64-linux/__init__.py +57 -0
build/torch210-cpu-x86_64-linux/_ops.py +9 -0
build/torch210-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch210-cpu-x86_64-linux/layers.py +41 -0
build/torch210-cpu-x86_64-linux/metadata.json +33 -0
build/torch210-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch210-cpu-x86_64-linux/symbols.json +103 -0
build/torch211-cpu-x86_64-linux/__init__.py +57 -0
build/torch211-cpu-x86_64-linux/_ops.py +9 -0
build/torch211-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch211-cpu-x86_64-linux/layers.py +41 -0
build/torch211-cpu-x86_64-linux/metadata.json +33 -0
build/torch211-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch211-cpu-x86_64-linux/symbols.json +103 -0
build/torch212-cpu-x86_64-linux/__init__.py +57 -0
build/torch212-cpu-x86_64-linux/_ops.py +9 -0
build/torch212-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch212-cpu-x86_64-linux/layers.py +41 -0
build/torch212-cpu-x86_64-linux/metadata.json +33 -0
build/torch212-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch212-cpu-x86_64-linux/symbols.json +103 -0
build/torch213-cpu-x86_64-linux/__init__.py +57 -0
build/torch213-cpu-x86_64-linux/_ops.py +9 -0
build/torch213-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch213-cpu-x86_64-linux/layers.py +41 -0
build/torch213-cpu-x86_64-linux/metadata.json +33 -0
build/torch213-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch213-cpu-x86_64-linux/symbols.json +103 -0
build/torch214-cpu-x86_64-linux/__init__.py +57 -0
build/torch214-cpu-x86_64-linux/_ops.py +9 -0
build/torch214-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch214-cpu-x86_64-linux/layers.py +41 -0
build/torch214-cpu-x86_64-linux/metadata.json +33 -0
build/torch214-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch214-cpu-x86_64-linux/symbols.json +103 -0
build/torch215-cpu-x86_64-linux/__init__.py +57 -0
build/torch215-cpu-x86_64-linux/_ops.py +9 -0
build/torch215-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so +3 -0
build/torch215-cpu-x86_64-linux/layers.py +41 -0
build/torch215-cpu-x86_64-linux/metadata.json +33 -0
build/torch215-cpu-x86_64-linux/metadata.json.sigstore +1 -0
build/torch215-cpu-x86_64-linux/symbols.json +103 -0

build/torch210-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch210-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch210-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:f6592ec4366732e0dc43c26132427d9e667974d39d1e016ff431bacf61d3f8a3
+size 83680

build/torch210-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch210-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cpu"
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
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+      "_ops.py": "5qmt6HsPG2i5R0v5qJlrQxqmACiDXEJemIdtTxJasys=",
+      "_rotary_cpu_fe2bb66.abi3.so": "9lkuxDZnMuDcQ8JhMkJ9nmZ5dNOdHgFv9DG6z2HT+KM=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "EpjlrijTVQ0vzlVF+optcEsM4jDbLi/PwCXnnxqA+4E="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch210-cpu-x86_64-linux/metadata.json.sigstore ADDED Viewed

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build/torch210-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}

build/torch211-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch211-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch211-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:027623a204139b60f5fc885b1bfecca41b2e2a7a01e2a3e25051543a9d1af005
+size 83680

build/torch211-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch211-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cpu"
+  },
+  "digest": {
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+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "5qmt6HsPG2i5R0v5qJlrQxqmACiDXEJemIdtTxJasys=",
+      "_rotary_cpu_fe2bb66.abi3.so": "AnYjogQTm2D1/IhbG/7MpBsuKnoB4qPiUFFUOp0a8AU=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "EpjlrijTVQ0vzlVF+optcEsM4jDbLi/PwCXnnxqA+4E="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch211-cpu-x86_64-linux/metadata.json.sigstore ADDED Viewed

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build/torch211-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}

build/torch212-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch212-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch212-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:19bdc4770964fe58c858488584f020cc953b3d3910c6793be77e67dd524b8187
+size 83688

build/torch212-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch212-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cpu"
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "5qmt6HsPG2i5R0v5qJlrQxqmACiDXEJemIdtTxJasys=",
+      "_rotary_cpu_fe2bb66.abi3.so": "Gb3Edwlk/ljIWEiFhPAgzJU7PTkQxnk7535n3VJLgYc=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "EpjlrijTVQ0vzlVF+optcEsM4jDbLi/PwCXnnxqA+4E="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

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build/torch212-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}

build/torch213-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch213-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch213-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:13afb38bb1d1791a9e9614f49a9f9e48484426d4f6f49b32a4b34beb5531f7ac
+size 83688

build/torch213-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch213-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
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+    }
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+      "dirty": false
+    }
+  }
+}

build/torch213-cpu-x86_64-linux/metadata.json.sigstore ADDED Viewed

	@@ -0,0 +1 @@

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build/torch213-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}

build/torch214-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch214-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch214-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:6130a2cc30afa26afa0e4fac107f8af1af52649f2c60133741cc8ae86f54ebb4
+size 83688

build/torch214-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch214-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cpu"
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "5qmt6HsPG2i5R0v5qJlrQxqmACiDXEJemIdtTxJasys=",
+      "_rotary_cpu_fe2bb66.abi3.so": "YTCizDCvomr6Dk+sEH+K8a9SZJ8sYBM3QcyK6G9U67Q=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "EpjlrijTVQ0vzlVF+optcEsM4jDbLi/PwCXnnxqA+4E="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch214-cpu-x86_64-linux/metadata.json.sigstore ADDED Viewed

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build/torch214-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}

build/torch215-cpu-x86_64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,57 @@

+import torch
+from . import layers
+from ._ops import ops
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]

build/torch215-cpu-x86_64-linux/_ops.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import torch
+from . import _rotary_cpu_fe2bb66
+ops = torch.ops._rotary_cpu_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cpu_fe2bb66::{op_name}"

build/torch215-cpu-x86_64-linux/_rotary_cpu_fe2bb66.abi3.so ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:0e9baa7c059f2c24d7586818a717a51854696b5de5db8bcc447b8d25cabf1c9d
+size 83688

build/torch215-cpu-x86_64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,41 @@

+import torch
+import torch.nn as nn
+from ._ops import ops
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated

build/torch215-cpu-x86_64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "name": "rotary",
+  "id": "_rotary_cpu_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cpu"
+  },
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+      "_rotary_cpu_fe2bb66.abi3.so": "DpuqfAWfLCTXWGgYpxelGFRpa13l24vMRHuNJcq/HJ0=",
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+    }
+  },
+  "provenance": {
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+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
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+      "dirty": false
+    }
+  }
+}

build/torch215-cpu-x86_64-linux/metadata.json.sigstore ADDED Viewed

	@@ -0,0 +1 @@

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build/torch215-cpu-x86_64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,103 @@

+{
+  "schema_version": 1,
+  "module": "_rotary_cpu_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cpu_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}