Build uploaded using `kernels`.

build/torch210-cxx11-cu126-x86_64-linux/__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/{torch28-cxx11-cu128-x86_64-linux/deformable_detr/_deformable_detr_57c3d32.abi3.so → torch210-cxx11-cu126-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:488b575c5239b051da77051e49fe2b33d62574ed4cae68f71e0758527eee5536
-size 9908376
+oid sha256:983865cafc6b57fb51e47143078b330f21ceb02c4f0a0a4408cdca2c96d6bb72
+size 8541064

build/{torch28-cxx11-cu126-x86_64-linux/deformable_detr → torch210-cxx11-cu126-x86_64-linux}/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _deformable_detr_57c3d32
-ops = torch.ops._deformable_detr_57c3d32
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_deformable_detr_57c3d32::{op_name}"
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch210-cxx11-cu126-x86_64-linux/deformable_detr/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu126-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch210-cxx11-cu128-x86_64-linux/__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/torch210-cxx11-cu128-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5622c742bb45a864c22f78340b820f45651868ea8e34e6e4fa5f11ae99421901
+size 11524544

build/{torch28-cxx11-cu128-x86_64-linux/deformable_detr → torch210-cxx11-cu128-x86_64-linux}/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _deformable_detr_57c3d32
-ops = torch.ops._deformable_detr_57c3d32
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_deformable_detr_57c3d32::{op_name}"
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch210-cxx11-cu128-x86_64-linux/deformable_detr/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu128-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch210-cxx11-cu130-x86_64-linux/__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/{torch28-cxx11-cu129-x86_64-linux/deformable_detr/_deformable_detr_57c3d32.abi3.so → torch210-cxx11-cu130-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e5cd16143ec4df47d54c69fef2541ae9a03ac5f8c2c018526822f7ae321510d7
-size 9962640
+oid sha256:cc258c88b7ebdaa8ab9027b34b111677b6d19fef02d4db23cf7d9f05139ecdd6
+size 9808352

build/{torch28-cxx11-cu129-x86_64-linux/deformable_detr → torch210-cxx11-cu130-x86_64-linux}/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _deformable_detr_57c3d32
-ops = torch.ops._deformable_detr_57c3d32
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_deformable_detr_57c3d32::{op_name}"
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch210-cxx11-cu130-x86_64-linux/deformable_detr/__init__.py

@@ -0,0 +1,26 @@
+import ctypes
+import sys
+
+import importlib
+from pathlib import Path
+from types import ModuleType
+
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+
+
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch210-cxx11-cu130-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch28-cxx11-cu126-x86_64-linux/__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/{torch29-cxx11-cu126-x86_64-linux/deformable_detr/_deformable_detr_57c3d32.abi3.so → torch28-cxx11-cu126-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:00131225eeba3d13bf037c67017b3e1ff8ce61ba77e874af2f2dd817aec5f7b5
-size 6921080
+oid sha256:9e7f8052b26751544b2a4c8aab8af4ab90628823b85a64dcd79f6405de428361
+size 8535712

build/{torch29-cxx11-cu126-x86_64-linux/deformable_detr → torch28-cxx11-cu126-x86_64-linux}/_ops.py

@@ -1,9 +1,9 @@
 import torch
-from . import _deformable_detr_57c3d32
-ops = torch.ops._deformable_detr_57c3d32
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
 
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_deformable_detr_57c3d32::{op_name}"
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch28-cxx11-cu126-x86_64-linux/deformable_detr/__init__.py

@@ -1,46 +1,26 @@
-from typing import List
-import torch
+import ctypes
+import sys
 
-from ._ops import ops
-from . import layers
+import importlib
+from pathlib import Path
+from types import ModuleType
 
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
 
-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"]
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch28-cxx11-cu126-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch28-cxx11-cu128-x86_64-linux/__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/torch28-cxx11-cu128-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e81e1303c5583c4bf177b118ae1f32dc8e5c7c21edb5314147ea8f969ea001a0
+size 11523184

build/torch28-cxx11-cu128-x86_64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch28-cxx11-cu128-x86_64-linux/deformable_detr/__init__.py

@@ -1,46 +1,26 @@
-from typing import List
-import torch
+import ctypes
+import sys
 
-from ._ops import ops
-from . import layers
+import importlib
+from pathlib import Path
+from types import ModuleType
 
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
 
-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"]
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch28-cxx11-cu128-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch28-cxx11-cu129-x86_64-linux/__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/torch28-cxx11-cu129-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:86846cc3da17baceee74f2a1420fb466e4a2120447760b3898e99ac6aaf34683
+size 11581544

build/torch28-cxx11-cu129-x86_64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch28-cxx11-cu129-x86_64-linux/deformable_detr/__init__.py

@@ -1,46 +1,26 @@
-from typing import List
-import torch
+import ctypes
+import sys
 
-from ._ops import ops
-from . import layers
+import importlib
+from pathlib import Path
+from types import ModuleType
 
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
 
-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"]
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch28-cxx11-cu129-x86_64-linux/metadata.json

@@ -0,0 +1 @@
+{"python-depends":[]}

build/torch29-cxx11-cu126-x86_64-linux/__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/{torch28-cxx11-cu126-x86_64-linux/deformable_detr/_deformable_detr_57c3d32.abi3.so → torch29-cxx11-cu126-x86_64-linux/_deformable_detr_7ba5e9c.abi3.so}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:849b408dcea47846a61de3e2c5dc178297e38ac85542e99d737887da93b199e6
-size 6920920
+oid sha256:ef56a6b25a1798b09cb41bf7f0e5afd3ac1681edff68e0a576f83b6cef9dea1d
+size 8535872

build/torch29-cxx11-cu126-x86_64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _deformable_detr_7ba5e9c
+ops = torch.ops._deformable_detr_7ba5e9c
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_deformable_detr_7ba5e9c::{op_name}"

build/torch29-cxx11-cu126-x86_64-linux/deformable_detr/__init__.py

@@ -1,46 +1,26 @@
-from typing import List
-import torch
+import ctypes
+import sys
 
-from ._ops import ops
-from . import layers
+import importlib
+from pathlib import Path
+from types import ModuleType
 
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
 
-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"]
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))