rename to gsplat (#30)

.github/workflows/core_tests.yml

@@ -25,6 +25,6 @@ jobs:
           pip install torch==2.0.0 --index-url https://download.pytorch.org/whl/cpu
           BUILD_NO_CUDA=1 pip install .
       - name: Run Black Format Check
-        run: black . diff_rast/ tests/ examples/ --check
+        run: black . gsplat/ tests/ examples/ --check
       - name: Run Tests.
         run: pytest tests/

.gitmodules

@@ -1,3 +1,3 @@
-[submodule "diff_rast/cuda/csrc/third_party/glm"]
-	path = diff_rast/cuda/csrc/third_party/glm
+[submodule "gsplat/cuda/csrc/third_party/glm"]
+	path = gsplat/cuda/csrc/third_party/glm
 	url = https://github.com/g-truc/glm.git

MANIFEST.in

@@ -1 +1 @@
-recursive-include diff_rast/cuda/csrc *
+recursive-include gsplat/cuda/csrc *

README.md

@@ -1,4 +1,4 @@
-# diff_rast
+# gsplat
 
 Our version of differentiable gaussian rasterizer
 
@@ -40,7 +40,7 @@ The curret tests that will be triggered by PR:
 Because we check for black formatting, it is recommend to run black before commit in the code:
 
 ```bash
-black . diff_rast/ tests/ examples/
+black . gsplat/ tests/ examples/
 ```
 
 Since there is no GPU supported on github workflow container, we don't test against those cuda unit tests under `tests/` in PR. So it is recommended to check test pass locally before committing:
@@ -67,11 +67,11 @@ sphinx-build docs/source _build
 
 # Brief walkthrough
 
-The main python bindings for rasterization are found by importing diff_rast
+The main python bindings for rasterization are found by importing gsplat
 
 ```
-import diff_rast
-help(diff_rast)
+import gsplat
+help(gsplat)
 ```
 
 # clangd setup (for Neovim)
@@ -117,7 +117,7 @@ sudo apt install bear
 #
 # This will save a file at 3dgs-exercise/compile_commands.json, which clangd
 # should be able to detect.
-bear -- pip install -e diff_rast/
+bear -- pip install -e gsplat/
 
 # Make sure the file is not empty!
 cat compile_commands.json

docs/source/apis/proj.rst

@@ -1,7 +1,7 @@
 ProjectGaussians
 ===================================
 
-.. currentmodule:: diff_rast
+.. currentmodule:: gsplat
 
 Given 3D gaussians parametrized by means :math:`μ`, covariances :math:`Σ`, colors :math:`c`, and opacities :math:`o`, the 
 ProjectGaussians function computes the projected 2D gaussians in the camera frame with means :math:`μ'`, covariances :math:`Σ'`, and depths :math:`z`

docs/source/apis/rast.rst

@@ -1,7 +1,7 @@
 RasterizeGaussians
 ===================================
 
-.. currentmodule:: diff_rast
+.. currentmodule:: gsplat
 
 Given 2D gaussians that are parametrized by their means :math:`μ'` and covariances :math:`Σ'` as well as their radii and conic parameters,
 the RasterizeGaussians function first sorts each gaussian such that all gaussians within the bounds of a tile are grouped and sorted by increasing depth :math:`z`,

docs/source/apis/utils.rst

@@ -3,7 +3,7 @@ Utils
 In addition to the main projection and rasterization functions, a few CUDA kernel and helper functions are exposed to python with the following bindings:
 
 
-.. currentmodule:: diff_rast
+.. currentmodule:: gsplat
 
 .. autoclass:: BinAndSortGaussians
 

docs/source/conf.py

@@ -1,11 +1,11 @@
 __version__ = None
-exec(open("../../diff_rast/version.py", "r").read())
+exec(open("../../gsplat/version.py", "r").read())
 
 # -- Project information
 
-project = "diff_rast"
-copyright = "2023, Vickie"
-author = "Vickie"
+project = "gsplat"
+copyright = "2023, nerfstudio team"
+author = "nerfstudio"
 
 release = __version__
 

docs/source/conventions/data_conventions.rst

@@ -1,7 +1,7 @@
 Data Conventions
 ===================================
 
-.. currentmodule:: diff_rast
+.. currentmodule:: gsplat
 
 Here we explain the various data conventions used in our repo.
 

docs/source/examples/simple_trainer.rst

@@ -1,7 +1,7 @@
 Simple Trainer
 ===================================
 
-.. currentmodule:: diff_rast
+.. currentmodule:: gsplat
 
 Training on an image
 -----------------------------------

docs/source/index.rst

@@ -1,4 +1,4 @@
-diff_rast
+gsplat
 ===================================
 
 .. image:: imgs/training.gif
@@ -8,7 +8,7 @@ diff_rast
 Overview
 --------
 
-*diff_rast* is an open-source library for CUDA accelerated rasterization of gaussians with python bindings. It is inspired by the SIGGRAPH paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields" :cite:p:`kerbl3Dgaussians`.
+*gsplat* is an open-source library for CUDA accelerated rasterization of gaussians with python bindings. It is inspired by the SIGGRAPH paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields" :cite:p:`kerbl3Dgaussians`.
 This libary contains the neccessary components for efficient 3D to 2D projection, sorting, and alpha compositing of gaussians and their associated backward passes for inverse rendering.
 
 Contributing

examples/simple_trainer.py

@@ -7,8 +7,8 @@
 import numpy as np
 import torch
 import tyro
-from diff_rast.project_gaussians import ProjectGaussians
-from diff_rast.rasterize import RasterizeGaussians
+from gsplat.project_gaussians import ProjectGaussians
+from gsplat.rasterize import RasterizeGaussians
 from PIL import Image
 from torch import Tensor, optim
 

diff_rast/bin_and_sort_gaussians.py → gsplat/bin_and_sort_gaussians.py

@@ -6,7 +6,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class BinAndSortGaussians(Function):

diff_rast/compute_cumulative_intersects.py → gsplat/compute_cumulative_intersects.py

@@ -6,7 +6,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class ComputeCumulativeIntersects(Function):

diff_rast/cov2d_bounds.py → gsplat/cov2d_bounds.py

@@ -7,7 +7,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class ComputeCov2dBounds(Function):

diff_rast/cuda/_backend.py → gsplat/cuda/_backend.py

@@ -33,7 +33,7 @@ def cuda_toolkit_version():
     return cuda_version
 
 
-name = "diff_rast_cuda"
+name = "gsplat_cuda"
 build_dir = _get_build_directory(name, verbose=False)
 extra_include_paths = [os.path.join(PATH, "csrc/third_party/glm")]
 extra_cflags = ["-O3"]
@@ -53,7 +53,7 @@ def cuda_toolkit_version():
 
 try:
     # try to import the compiled module (via setup.py)
-    from diff_rast import csrc as _C
+    from gsplat import csrc as _C
 except ImportError:
     # if failed, try with JIT compilation
     if cuda_toolkit_available():

diff_rast/cuda/csrc/CMakeLists.txt → gsplat/cuda/csrc/CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.12)  # You can adjust the minimum required version
 set(CMAKE_CUDA_ARCHITECTURES 70 75 89)  # Ti 2080 uses 75. V100 uses 70. RTX 4090 uses 89.
 
-project(diff_rast CXX CUDA)
+project(gsplat CXX CUDA)
 set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_CXX_EXTENSIONS OFF)
 set(CMAKE_CUDA_STANDARD 17)

diff_rast/get_tile_bin_edges.py → gsplat/get_tile_bin_edges.py

@@ -6,7 +6,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class GetTileBinEdges(Function):

diff_rast/map_gaussian_to_intersects.py → gsplat/map_gaussian_to_intersects.py

@@ -6,7 +6,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class MapGaussiansToIntersects(Function):

diff_rast/project_gaussians.py → gsplat/project_gaussians.py

@@ -6,7 +6,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class ProjectGaussians(Function):

diff_rast/rasterize.py → gsplat/rasterize.py

@@ -7,7 +7,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class RasterizeGaussians(Function):

diff_rast/rasterize_forward_kernel.py → gsplat/rasterize_forward_kernel.py

@@ -7,7 +7,7 @@
 from torch import Tensor
 from torch.autograd import Function
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 
 class RasterizeForwardKernel(Function):

diff_rast/sh.py → gsplat/sh.py

@@ -1,6 +1,6 @@
 """Python bindings for SH"""
 
-import diff_rast.cuda as _C
+import gsplat.cuda as _C
 
 from jaxtyping import Float
 from torch import Tensor

setup.py

@@ -7,7 +7,7 @@
 from setuptools import find_packages, setup
 
 __version__ = None
-exec(open("diff_rast/version.py", "r").read())
+exec(open("gsplat/version.py", "r").read())
 
 URL = ""  # TODO
 
@@ -26,7 +26,7 @@ def get_extensions():
     from torch.__config__ import parallel_info
     from torch.utils.cpp_extension import CUDAExtension
 
-    extensions_dir = osp.join("diff_rast", "cuda", "csrc")
+    extensions_dir = osp.join("gsplat", "cuda", "csrc")
     sources = glob.glob(osp.join(extensions_dir, "*.cu")) + glob.glob(
         osp.join(extensions_dir, "*.cpp")
     )
@@ -44,7 +44,7 @@ def get_extensions():
     define_macros = []
 
     if sys.platform == "win32":
-        define_macros += [("diff_rast_EXPORTS", None)]
+        define_macros += [("gsplat_EXPORTS", None)]
 
     extra_compile_args = {"cxx": ["-O3"]}
     if not os.name == "nt":  # Not on Windows:
@@ -83,7 +83,7 @@ def get_extensions():
     extra_compile_args["nvcc"] = nvcc_flags
 
     extension = CUDAExtension(
-        f"diff_rast.csrc",
+        f"gsplat.csrc",
         sources,
         include_dirs=[osp.join(extensions_dir, "third_party", "glm")],
         define_macros=define_macros,
@@ -96,7 +96,7 @@ def get_extensions():
 
 
 setup(
-    name="diff_rast",
+    name="gsplat",
     version=__version__,
     description=" Python package for differentiable rasterization of gaussians",
     keywords="gaussian, splatting, cuda",
@@ -110,7 +110,7 @@ def get_extensions():
         "typing_extensions; python_version<'3.8'",
     ],
     extras_require={
-        # dev dependencies. Install them by `pip install diff_rast[dev]`
+        # dev dependencies. Install them by `pip install gsplat[dev]`
         "dev": [
             "black[jupyter]==22.3.0",
             "isort==5.10.1",

tests/test_bin_and_sort_gaussians.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_bin_and_sort_gaussians():
-    from diff_rast import _torch_impl
-    from diff_rast.bin_and_sort_gaussians import BinAndSortGaussians
+    from gsplat import _torch_impl
+    from gsplat.bin_and_sort_gaussians import BinAndSortGaussians
 
     torch.manual_seed(42)
 

tests/test_cov2d_bounds.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_compare_binding_to_pytorch():
-    from diff_rast._torch_impl import compute_cov2d_bounds as _compute_cov2d_bounds
-    from diff_rast.cov2d_bounds import ComputeCov2dBounds
+    from gsplat._torch_impl import compute_cov2d_bounds as _compute_cov2d_bounds
+    from gsplat.cov2d_bounds import ComputeCov2dBounds
 
     torch.manual_seed(42)
 

tests/test_cumulative_intersects.py

@@ -7,7 +7,7 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_cumulative_intersects():
-    from diff_rast.compute_cumulative_intersects import ComputeCumulativeIntersects
+    from gsplat.compute_cumulative_intersects import ComputeCumulativeIntersects
 
     torch.manual_seed(42)
 

tests/test_get_tile_bin_edges.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_get_tile_bin_edges():
-    from diff_rast import _torch_impl
-    from diff_rast.get_tile_bin_edges import GetTileBinEdges
+    from gsplat import _torch_impl
+    from gsplat.get_tile_bin_edges import GetTileBinEdges
 
     torch.manual_seed(42)
 

tests/test_map_gaussians.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_map_gaussians():
-    from diff_rast import _torch_impl
-    from diff_rast.map_gaussian_to_intersects import MapGaussiansToIntersects
+    from gsplat import _torch_impl
+    from gsplat.map_gaussian_to_intersects import MapGaussiansToIntersects
 
     torch.manual_seed(42)
 

tests/test_project_gaussians.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_project_gaussians_forward():
-    from diff_rast import _torch_impl
-    import diff_rast.cuda as _C
+    from gsplat import _torch_impl
+    import gsplat.cuda as _C
 
     torch.manual_seed(42)
 

tests/test_rasterize_forward_kernel.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_rasterize_forward_kernel():
-    from diff_rast import _torch_impl
-    from diff_rast.rasterize_forward_kernel import RasterizeForwardKernel
+    from gsplat import _torch_impl
+    from gsplat.rasterize_forward_kernel import RasterizeForwardKernel
 
     torch.manual_seed(42)
 

tests/test_sh.py

@@ -7,8 +7,8 @@
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="No CUDA device")
 def test_sh():
-    from diff_rast import _torch_impl
-    from diff_rast import sh
+    from gsplat import _torch_impl
+    from gsplat import sh
 
     num_points = 1
     degree = 4