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fVDB changes including:
•Reintroduced missing src/build/* files that were accidentally ommitted •JaggedTensor concatentation moved to a cuda kernel •Non-cumulative indices for ijk mappings is now the default return style (makes indexing into JaggedTensors of data more natural) •cuDNN disabled for CUDA versions <12 •Updated notebook files to new API and now included •Removed deprecated usage of `python setup.py test` and running pytest directly Signed-off-by: Jonathan Swartz <[email protected]>
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‎fvdb/.gitignore

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@@ -1,5 +1,4 @@
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build/*
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build/
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/build/*
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*.creator
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*.includes
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*.files

‎fvdb/README.md

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@@ -93,7 +93,7 @@ pip install .
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To make sure that everything works by running tests:
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```shell
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python setup.py test
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pytest tests/unit
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```
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### Building Documentation
@@ -118,7 +118,7 @@ docker run -it --gpus all --rm \
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--mount type=bind,source="$HOME/.ssh",target=/root/.ssh \
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--mount type=bind,source="$(pwd)",target=/fvdb \
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fvdb-dev:latest \
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conda run -n fvdb_test --no-capture-output python setup.py test
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conda run -n fvdb_test --no-capture-output python setup.py develop
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```
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‎fvdb/env/build_environment.yml

Lines changed: 7 additions & 5 deletions
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@@ -2,18 +2,20 @@ name: fvdb_build
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channels:
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- nvidia/label/cuda-12.1.0
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- pytorch
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- conda-forge
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dependencies:
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- python=3.10
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- pytorch=2.2
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- pytorch-cuda=12.1
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- pytorch::pytorch=2.2
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- pytorch::pytorch-cuda=12.1
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- git
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- gitpython
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- ca-certificates
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- certifi
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- openssl
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- cuda
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- cuda-nvcc
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- nvidia/label/cuda-12.1.0::cuda
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- nvidia/label/cuda-12.1.0::cuda-tools
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- nvidia/label/cuda-12.1.0::cuda-nvcc
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- nvidia/label/cuda-12.1.0::cuda-cccl
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- nvidia/label/cuda-12.1.0::cuda-libraries-static
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- gcc_linux-64=11
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- gxx_linux-64=11
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- setuptools

‎fvdb/env/cutlass.patch

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,7 @@ index e22c8be3..a29e6067 100644
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storage = reinterpret_cast<uint16_t const &>(x);
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#else
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- __half_raw raw(x);
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+ __half_raw raw(*(reinterpret_cast<const unsigned short*>(&x)));
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+ __half_raw raw(*(reinterpret_cast<const __half_raw*>(&x)));
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std::memcpy(&storage, &raw.x, sizeof(storage));
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#endif
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}
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storage = reinterpret_cast<uint16_t const &>(x);
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#else
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- __half_raw raw(x);
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+ __half_raw raw(*(reinterpret_cast<const unsigned short*>(&x)));
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+ __half_raw raw(*(reinterpret_cast<const __half_raw*>(&x)));
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std::memcpy(&storage, &raw.x, sizeof(storage));
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#endif
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return *this;

‎fvdb/env/test_environment.yml

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Original file line numberDiff line numberDiff line change
@@ -3,20 +3,22 @@ channels:
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- pyg
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- nvidia/label/cuda-12.1.0
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- pytorch
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- conda-forge
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dependencies:
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- python=3.10
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- pytorch=2.2
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- pytorch-cuda=12.1
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- pytorch::pytorch=2.2
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- pytorch::pytorch-cuda=12.1
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- tensorboard
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- pip
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- git
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- gitpython
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- ca-certificates
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- certifi
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- openssl
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- cuda
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- cuda-nvcc
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- nvidia/label/cuda-12.1.0::cuda
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- nvidia/label/cuda-12.1.0::cuda-tools
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- nvidia/label/cuda-12.1.0::cuda-nvcc
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- nvidia/label/cuda-12.1.0::cuda-cccl
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- nvidia/label/cuda-12.1.0::cuda-libraries-static
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- parameterized
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- gcc_linux-64=11
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- gxx_linux-64=11

‎fvdb/fvdb/_Cpp.pyi

Lines changed: 19 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -118,7 +118,9 @@ class JaggedTensor:
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@property
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def dtype(self) -> torch.dtype: ...
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@property
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def jidx(self) -> torch.ShortTensor: ...
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def jidx(self) -> torch.IntTensor: ...
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@property
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def jlidx(self) -> torch.IntTensor: ...
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@property
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def joffsets(self) -> torch.LongTensor: ...
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@property
@@ -134,6 +136,19 @@ class JaggedTensor:
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@property
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def requires_grad(self) -> bool: ...
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@staticmethod
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def from_data_and_indices(data: torch.Tensor, indices: torch.Tensor, num_tensors: int) -> JaggedTensor: ...
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@staticmethod
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def from_data_indices_and_list_ids(data: torch.Tensor, indices: torch.Tensor, list_ids: torch.Tensor, num_tensors: int) -> JaggedTensor: ...
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@staticmethod
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def from_data_and_offsets(data: torch.Tensor, offsets: torch.Tensor) -> JaggedTensor: ...
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@staticmethod
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def from_data_offsets_and_list_ids(data: torch.Tensor, offsets: torch.Tensor, list_ids: torch.Tensor) -> JaggedTensor: ...
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JaggedTensorOrTensor = Union[torch.Tensor, JaggedTensor]
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class GridBatch:
@@ -243,8 +258,8 @@ class GridBatch:
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def cubes_in_grid(self, cube_centers: JaggedTensorOrTensor, cube_min: Vec3dOrScalar = 0.0, cube_max: Vec3dOrScalar = 0.0, ignore_disabled: bool = False) -> JaggedTensor: ...
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def cubes_intersect_grid(self, cube_centers: JaggedTensorOrTensor, cube_min: Vec3dOrScalar = 0.0, cube_max: Vec3dOrScalar = 0.0, ignore_disabled: bool = False) -> JaggedTensor: ...
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def ijk_to_index(self, ijk: JaggedTensorOrTensor) -> JaggedTensor: ...
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def ijk_to_inv_index(self, ijk: JaggedTensorOrTensor) -> JaggedTensor: ...
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def ijk_to_index(self, ijk: JaggedTensorOrTensor, cumulative: bool = False) -> JaggedTensor: ...
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def ijk_to_inv_index(self, ijk: JaggedTensorOrTensor, cumulative: bool = False) -> JaggedTensor: ...
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def neighbor_indexes(self, ijk: JaggedTensorOrTensor, extent: int, bitshift: int = 0) -> JaggedTensor: ...
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def splat_bezier(self, points: JaggedTensorOrTensor, points_data: JaggedTensorOrTensor) -> JaggedTensor: ...
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def segments_along_rays(self, ray_origins: JaggedTensorOrTensor, ray_directions: JaggedTensorOrTensor, max_segments: int, eps: float = 0.0, ignore_masked: bool = False) -> JaggedTensor: ...
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def voxels_along_rays(self, ray_origins: JaggedTensorOrTensor, ray_directions: JaggedTensorOrTensor, max_voxels: int, eps: float = 0.0, return_ijk: bool = True) -> Tuple[JaggedTensor, JaggedTensor]: ...
274+
def voxels_along_rays(self, ray_origins: JaggedTensorOrTensor, ray_directions: JaggedTensorOrTensor, max_voxels: int, eps: float = 0.0, return_ijk: bool = True, cumulative: bool = False) -> Tuple[JaggedTensor, JaggedTensor]: ...
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def uniform_ray_samples(self, ray_origins: JaggedTensorOrTensor, ray_directions: JaggedTensorOrTensor, t_min: JaggedTensorOrTensor, t_max: JaggedTensorOrTensor, step_size: float, cone_angle: float = 0.0, include_end_segments : bool = True, return_midpoints: bool = False, eps: float = 0.0) -> JaggedTensor: ...
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def ray_implicit_intersection(self, ray_origins: JaggedTensorOrTensor, ray_directions: JaggedTensorOrTensor, grid_scalars: JaggedTensorOrTensor, eps: float = 0.0) -> JaggedTensor: ...
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‎fvdb/fvdb/nn/vdbtensor.py

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@@ -71,7 +71,7 @@ def _feature_ops(op, other: List[Union["VDBTensor", JaggedTensor, Any]]):
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raw_features.append(o.feature.jdata)
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elif isinstance(o, JaggedTensor):
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assert pivot_tensor.total_voxels == o.jdata.size(0), "All tensors should have the same voxels"
74-
assert pivot_tensor.grid.grid_count == len(o.joffsets), "All tensors should have the same batch size"
74+
assert pivot_tensor.grid.grid_count == o.num_tensors, "All tensors should have the same batch size"
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raw_features.append(o.jdata)
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else:
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raw_features.append(o)

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