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kernels-bot commited on 10 days ago

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3598495

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build/torch210-cu126-aarch64-linux/__init__.py +46 -0
build/torch210-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch210-cu126-aarch64-linux/_ops.py +9 -0
build/torch210-cu126-aarch64-linux/layers.py +84 -0
build/torch210-cu126-aarch64-linux/metadata.json +43 -0
build/torch210-cu126-aarch64-linux/metadata.json.sigstore +1 -0
build/torch210-cu126-aarch64-linux/symbols.json +138 -0
build/torch210-cu128-aarch64-linux/__init__.py +46 -0
build/torch210-cu128-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch210-cu128-aarch64-linux/_ops.py +9 -0
build/torch210-cu128-aarch64-linux/layers.py +84 -0
build/torch210-cu128-aarch64-linux/metadata.json +46 -0
build/torch210-cu128-aarch64-linux/metadata.json.sigstore +1 -0
build/torch210-cu128-aarch64-linux/symbols.json +138 -0
build/torch210-cu130-aarch64-linux/__init__.py +46 -0
build/torch210-cu130-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch210-cu130-aarch64-linux/_ops.py +9 -0
build/torch210-cu130-aarch64-linux/layers.py +84 -0
build/torch210-cu130-aarch64-linux/metadata.json +46 -0
build/torch210-cu130-aarch64-linux/metadata.json.sigstore +1 -0
build/torch210-cu130-aarch64-linux/symbols.json +138 -0
build/torch211-cu126-aarch64-linux/__init__.py +46 -0
build/torch211-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch211-cu126-aarch64-linux/_ops.py +9 -0
build/torch211-cu126-aarch64-linux/layers.py +84 -0
build/torch211-cu126-aarch64-linux/metadata.json +43 -0
build/torch211-cu126-aarch64-linux/metadata.json.sigstore +1 -0
build/torch211-cu126-aarch64-linux/symbols.json +138 -0
build/torch211-cu128-aarch64-linux/__init__.py +46 -0
build/torch211-cu128-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch211-cu128-aarch64-linux/_ops.py +9 -0
build/torch211-cu128-aarch64-linux/layers.py +84 -0
build/torch211-cu128-aarch64-linux/metadata.json +46 -0
build/torch211-cu128-aarch64-linux/metadata.json.sigstore +1 -0
build/torch211-cu128-aarch64-linux/symbols.json +138 -0
build/torch211-cu130-aarch64-linux/__init__.py +46 -0
build/torch211-cu130-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch211-cu130-aarch64-linux/_ops.py +9 -0
build/torch211-cu130-aarch64-linux/layers.py +84 -0
build/torch211-cu130-aarch64-linux/metadata.json +46 -0
build/torch211-cu130-aarch64-linux/metadata.json.sigstore +1 -0
build/torch211-cu130-aarch64-linux/symbols.json +138 -0
build/torch212-cu126-aarch64-linux/__init__.py +46 -0
build/torch212-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so +3 -0
build/torch212-cu126-aarch64-linux/_ops.py +9 -0
build/torch212-cu126-aarch64-linux/layers.py +84 -0
build/torch212-cu126-aarch64-linux/metadata.json +43 -0
build/torch212-cu126-aarch64-linux/metadata.json.sigstore +1 -0
build/torch212-cu126-aarch64-linux/symbols.json +138 -0
build/torch212-cu130-aarch64-linux/__init__.py +46 -0

build/torch210-cu126-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch210-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:44601388b33d55f8b48b7c95f533b37454bac4f3eef7ee31268883830e30d677
+size 6661560

build/torch210-cu126-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch210-cu126-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch210-cu126-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "RGATiLM9Vfi0i3yV9TOzdFS6xPPu9+4xJoiDgw4w1nc=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

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build/torch210-cu126-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
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+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
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+            "name": "value",
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+            "default": null,
+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch210-cu128-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch210-cu128-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:922220e4936bc46ac0122b268dc6f69a3bba4253506ee07a170eef0407aa3e91
+size 9610648

build/torch210-cu128-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch210-cu128-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch210-cu128-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "kiIg5JNrxGrAEismjcb2mju6QlNQbuB6Fw7vBAeqPpE=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch210-cu128-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch210-cu128-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
+    {
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
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+            "default": null,
+            "annotation": "int"
+          }
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+        "return_annotation": "torch.Tensor"
+      }
+    },
+    {
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
+          },
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+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch210-cu130-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch210-cu130-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:afe3c348831bd99e29054691a0cc6553260b5de61c1f741fcf2ee391a6918c7c
+size 9846400

build/torch210-cu130-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch210-cu130-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch210-cu130-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "r+PDSIMb2Z4pBUaRoMxlUyYLXeYcH3Qfzy7jkaaRjHw=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch210-cu130-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch210-cu130-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
+    {
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+          {
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+            "kind": "POSITIONAL_OR_KEYWORD",
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+            "annotation": "int"
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+        "return_annotation": "torch.Tensor"
+      }
+    },
+    {
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch211-cu126-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch211-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:18bff04b08a2cacd337075275093a54a208f1f02620fc032872edd94d9600830
+size 6661672

build/torch211-cu126-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch211-cu126-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch211-cu126-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "GL/wSwiiys0zcHUnUJOlSiCPHwJiD8Ayhy7dlNlgCDA=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch211-cu126-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch211-cu126-aarch64-linux/symbols.json ADDED Viewed

	@@ -0,0 +1,138 @@

+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
+    {
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
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+            "annotation": "int"
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+        "return_annotation": "torch.Tensor"
+      }
+    },
+    {
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
+          },
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+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch211-cu128-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch211-cu128-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:9bcc9b35c9549366b29ca0e54770644a49535ff1892166b3362020f7236e2c9a
+size 9610768

build/torch211-cu128-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch211-cu128-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch211-cu128-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "m8ybNclUk2aynKDlR3BkSklTX/GJIWazNiAg9yNuLJo=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch211-cu128-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch211-cu128-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
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+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+          {
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+        "return_annotation": "torch.Tensor"
+      }
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
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+            "name": "value",
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+            "annotation": "torch.Tensor"
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+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch211-cu130-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch211-cu130-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:b7c42f6f89e6b97f83c49ec4265ca7658bfc96e18f8ce0062017a8219a320446
+size 9846512

build/torch211-cu130-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch211-cu130-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch211-cu130-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "t8Qvb4nmuX+DxJ7EJlynZYv8luGPjOAGIBeoIZoyBEY=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch211-cu130-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch211-cu130-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+          {
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+        "return_annotation": "torch.Tensor"
+      }
+    },
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
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+            "name": "value",
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+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch212-cu126-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]

build/torch212-cu126-aarch64-linux/_deformable_detr_cuda_fe2bb66.abi3.so ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:b1c54e6542d1ce54d8c64138f8c42f261303bcc65fa7d6b0d1b114f9c6407905
+size 6661240

build/torch212-cu126-aarch64-linux/_ops.py ADDED Viewed

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

+import torch
+from . import _deformable_detr_cuda_fe2bb66
+ops = torch.ops._deformable_detr_cuda_fe2bb66
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_cuda_fe2bb66::{op_name}"

build/torch212-cu126-aarch64-linux/layers.py ADDED Viewed

	@@ -0,0 +1,84 @@

+from typing import List, Union, Tuple
+from torch import Tensor
+from torch.autograd import Function
+from torch.autograd.function import once_differentiable
+import torch.nn as nn
+from ._ops import ops
+class MultiScaleDeformableAttentionFunction(Function):
+    @staticmethod
+    def forward(
+        context,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        context.im2col_step = im2col_step
+        output = ops.ms_deform_attn_forward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            context.im2col_step,
+        )
+        context.save_for_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        )
+        return output
+    @staticmethod
+    @once_differentiable
+    def backward(context, grad_output):
+        (
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+        ) = context.saved_tensors
+        grad_value, grad_sampling_loc, grad_attn_weight = ops.ms_deform_attn_backward(
+            value,
+            value_spatial_shapes,
+            value_level_start_index,
+            sampling_locations,
+            attention_weights,
+            grad_output,
+            context.im2col_step,
+        )
+        return grad_value, None, None, grad_sampling_loc, grad_attn_weight, None
+class MultiScaleDeformableAttention(nn.Module):
+    def forward(
+        self,
+        value: Tensor,
+        value_spatial_shapes: Tensor,
+        value_spatial_shapes_list: List[Tuple],
+        level_start_index: Tensor,
+        sampling_locations: Tensor,
+        attention_weights: Tensor,
+        im2col_step: int,
+    ):
+        return MultiScaleDeformableAttentionFunction.apply(
+            value,
+            value_spatial_shapes,
+            level_start_index,
+            sampling_locations,
+            attention_weights,
+            im2col_step,
+        )
+__all__ = ["MultiScaleDeformableAttention"]

build/torch212-cu126-aarch64-linux/metadata.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "name": "deformable-detr",
+  "id": "_deformable_detr_cuda_fe2bb66",
+  "version": 1,
+  "kernels-minver": "0.14.0",
+  "license": "Apache-2.0",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "/P9rmKjjgzhOqU3peSjUIi0u9GaxAmMEcaQb5kNGG90=",
+      "_deformable_detr_cuda_fe2bb66.abi3.so": "scVOZULRzlTYxkE4+MQvJhMDvMZfp9aw0bEU+cZAeQU=",
+      "_ops.py": "i9uA2K4/sWeUF4FAwHQJ80J8tvwwaf5I4n6oN+q9VR4=",
+      "layers.py": "H3mypbDteagvzG5WTscmD05BfJhNbylbPJr0zb3k82A=",
+      "symbols.json": "SE1abIt8U28b3HcQzThCV+v19Ww2kNiQdWEjoQzsUpw="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}

build/torch212-cu126-aarch64-linux/metadata.json.sigstore ADDED Viewed

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build/torch212-cu126-aarch64-linux/symbols.json ADDED Viewed

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+{
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+  "module": "_deformable_detr_cuda_fe2bb66",
+  "functions": [
+    {
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+      "qualname": "ms_deform_attn_forward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "spatial_shapes",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "level_start_index",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sampling_loc",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "attn_weight",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
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+            "kind": "POSITIONAL_OR_KEYWORD",
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+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "torch.Tensor"
+      }
+    },
+    {
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+      "qualname": "ms_deform_attn_backward",
+      "module": "_deformable_detr_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "value",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+            "annotation": "torch.Tensor"
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+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "grad_output",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "im2col_step",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "List[torch.Tensor]"
+      }
+    }
+  ],
+  "layers": [
+    {
+      "name": "MultiScaleDeformableAttention",
+      "qualname": "MultiScaleDeformableAttention",
+      "module": "_deformable_detr_cuda_fe2bb66.layers",
+      "kind": "class",
+      "doc": "Base class for all neural network modules.\n\nYour models should also subclass this class.\n\nModules can also contain other Modules, allowing them to be nested in\na tree structure. You can assign the submodules as regular attributes::\n\n    import torch.nn as nn\n    import torch.nn.functional as F\n\n\n    class Model(nn.Module):\n        def __init__(self) -> None:\n            super().__init__()\n            self.conv1 = nn.Conv2d(1, 20, 5)\n            self.conv2 = nn.Conv2d(20, 20, 5)\n\n        def forward(self, x):\n            x = F.relu(self.conv1(x))\n            return F.relu(self.conv2(x))\n\nSubmodules assigned in this way will be registered, and will also have their\nparameters converted when you call :meth:`to`, etc.\n\n.. note::\n    As per the example above, an ``__init__()`` call to the parent class\n    must be made before assignment on the child.\n\n:ivar training: Boolean represents whether this module is in training or\n                evaluation mode.\n:vartype training: bool",
+      "signature": {
+        "parameters": [
+          {
+            "name": "args",
+            "kind": "VAR_POSITIONAL",
+            "default": null,
+            "annotation": "Any"
+          },
+          {
+            "name": "kwargs",
+            "kind": "VAR_KEYWORD",
+            "default": null,
+            "annotation": "Any"
+          }
+        ],
+        "return_annotation": "None"
+      },
+      "attributes": {
+        "has_backward": null,
+        "can_torch_compile": null
+      }
+    }
+  ]
+}

build/torch212-cu130-aarch64-linux/__init__.py ADDED Viewed

	@@ -0,0 +1,46 @@

+from typing import List
+import torch
+from ._ops import ops
+from . import layers
+def ms_deform_attn_backward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    grad_output: torch.Tensor,
+    im2col_step: int,
+) -> List[torch.Tensor]:
+    return ops.ms_deform_attn_backward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        grad_output,
+        im2col_step,
+    )
+def ms_deform_attn_forward(
+    value: torch.Tensor,
+    spatial_shapes: torch.Tensor,
+    level_start_index: torch.Tensor,
+    sampling_loc: torch.Tensor,
+    attn_weight: torch.Tensor,
+    im2col_step: int,
+) -> torch.Tensor:
+    return ops.ms_deform_attn_forward(
+        value,
+        spatial_shapes,
+        level_start_index,
+        sampling_loc,
+        attn_weight,
+        im2col_step,
+    )
+__all__ = ["layers", "ms_deform_attn_forward", "ms_deform_attn_backward"]