Build uploaded using `kernels`.

.gitattributes

@@ -42,3 +42,9 @@ build/torch28-cxx11-cu129-x86_64-linux/_cv_utils_8541a33.abi3.so filter=lfs diff
 build/torch29-cxx11-cu126-x86_64-linux/_cv_utils_8541a33.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch29-cxx11-cu128-x86_64-linux/_cv_utils_8541a33.abi3.so filter=lfs diff=lfs merge=lfs -text
 build/torch29-cxx11-cu130-x86_64-linux/_cv_utils_8541a33.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu126-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu128-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch210-cxx11-cu130-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu126-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu128-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text
+build/torch29-cxx11-cu130-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so filter=lfs diff=lfs merge=lfs -text

build/torch210-cxx11-cu126-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch210-cxx11-cu126-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dd70e0ed7915339cb40d62b2db8381331cf07586acdbeed4d7cd1bd06c54b6d5
+size 3168896

build/torch210-cxx11-cu126-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch210-cxx11-cu126-aarch64-linux/cv_utils/__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-aarch64-linux/metadata.json

@@ -0,0 +1,17 @@
+{
+  "version": 1,
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  }
+}

build/torch210-cxx11-cu128-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch210-cxx11-cu128-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2203c765753e697bad106474dc3536fd991024509abd6f4cbb2db1c7e9684857
+size 3824424

build/torch210-cxx11-cu128-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch210-cxx11-cu128-aarch64-linux/cv_utils/__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-aarch64-linux/metadata.json

@@ -0,0 +1,20 @@
+{
+  "version": 1,
+  "python-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"
+    ]
+  }
+}

build/torch210-cxx11-cu130-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch210-cxx11-cu130-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f62f22326656ca04093c8230d4a418d57f3ecbcfb6b939e9d13226d11dbe587e
+size 3633848

build/torch210-cxx11-cu130-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch210-cxx11-cu130-aarch64-linux/cv_utils/__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-aarch64-linux/metadata.json

@@ -0,0 +1,18 @@
+{
+  "version": 1,
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "11.0",
+      "12.0+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}

build/torch29-cxx11-cu126-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch29-cxx11-cu126-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bb8cff7b3e4834dcedbac0058de07b8b9a50a72e3d73a591710994b27c58fba3
+size 3165512

build/torch29-cxx11-cu126-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch29-cxx11-cu126-aarch64-linux/cv_utils/__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/torch29-cxx11-cu126-aarch64-linux/metadata.json

@@ -0,0 +1,17 @@
+{
+  "version": 1,
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  }
+}

build/torch29-cxx11-cu128-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch29-cxx11-cu128-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b8fa241565cfdede03164f1722d4e31307f9658aca61020deada6bed653e7a91
+size 3820720

build/torch29-cxx11-cu128-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch29-cxx11-cu128-aarch64-linux/cv_utils/__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/torch29-cxx11-cu128-aarch64-linux/metadata.json

@@ -0,0 +1,20 @@
+{
+  "version": 1,
+  "python-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"
+    ]
+  }
+}

build/torch29-cxx11-cu130-aarch64-linux/__init__.py

@@ -0,0 +1,12 @@
+import torch
+from typing import List
+
+from ._ops import ops
+
+def cc_2d(inputs: torch.Tensor, get_counts: bool) -> List[torch.Tensor]:
+    return ops.cc_2d(inputs, get_counts)
+
+def generic_nms(dets: torch.Tensor, scores: torch.Tensor, iou_threshold: float, use_iou_matrix: bool) -> torch.Tensor:
+    return ops.generic_nms(dets, scores, iou_threshold, use_iou_matrix)
+
+__all__ = ["cc_2d", "generic_nms"]

build/torch29-cxx11-cu130-aarch64-linux/_cv_utils_cuda_8cfc281.abi3.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d3eae36344c7f1472879d5df26ad7fc9826e7ae5fd99a89114d147a015f0d5c
+size 3630144

build/torch29-cxx11-cu130-aarch64-linux/_ops.py

@@ -0,0 +1,9 @@
+import torch
+from . import _cv_utils_cuda_8cfc281
+ops = torch.ops._cv_utils_cuda_8cfc281
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_cv_utils_cuda_8cfc281::{op_name}"

build/torch29-cxx11-cu130-aarch64-linux/cv_utils/__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/torch29-cxx11-cu130-aarch64-linux/metadata.json

@@ -0,0 +1,18 @@
+{
+  "version": 1,
+  "python-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "11.0",
+      "12.0+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  }
+}