Build (aarch64)

build/torch26-cxx11-cu126-aarch64-linux/deformable_detr/__init__.py

@@ -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/torch26-cxx11-cu126-aarch64-linux/deformable_detr/_deformable_detr_4f82c9e.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:486d6b3700e5d789c1d8d3225b9c681db33436d19341899e72a81f4675eb9a55
+size 6112328

build/torch26-cxx11-cu126-aarch64-linux/deformable_detr/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_4f82c9e
+ops = torch.ops._deformable_detr_4f82c9e
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_4f82c9e::{op_name}"

build/torch26-cxx11-cu126-aarch64-linux/deformable_detr/layers.py

@@ -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/torch26-cxx98-cu126-aarch64-linux/deformable_detr/__init__.py

@@ -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/torch26-cxx98-cu126-aarch64-linux/deformable_detr/_deformable_detr_4f82c9e.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34d28a81c3b5ae1fcb58583681644cf66072b67844bc21fe4649c17d01f4fce7
+size 6108976

build/torch26-cxx98-cu126-aarch64-linux/deformable_detr/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_4f82c9e
+ops = torch.ops._deformable_detr_4f82c9e
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_4f82c9e::{op_name}"

build/torch26-cxx98-cu126-aarch64-linux/deformable_detr/layers.py

@@ -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/torch27-cxx11-cu126-aarch64-linux/deformable_detr/__init__.py

@@ -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/torch27-cxx11-cu126-aarch64-linux/deformable_detr/_deformable_detr_4f82c9e.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:197a33ee4fd5ea29cb197a84d93eaa4cd9c852233b2ad5870337263c80c74b89
+size 6112552

build/torch27-cxx11-cu126-aarch64-linux/deformable_detr/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_4f82c9e
+ops = torch.ops._deformable_detr_4f82c9e
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_4f82c9e::{op_name}"

build/torch27-cxx11-cu126-aarch64-linux/deformable_detr/layers.py

@@ -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/torch27-cxx11-cu128-aarch64-linux/deformable_detr/__init__.py

@@ -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/torch27-cxx11-cu128-aarch64-linux/deformable_detr/_deformable_detr_4f82c9e.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:57aa50c458c3b61fdbcf7f64f7c3e70a9c78302fe4c72eff3f35e9a65edbf5d9
+size 5326200

build/torch27-cxx11-cu128-aarch64-linux/deformable_detr/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_4f82c9e
+ops = torch.ops._deformable_detr_4f82c9e
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_4f82c9e::{op_name}"

build/torch27-cxx11-cu128-aarch64-linux/deformable_detr/layers.py

@@ -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"]