Enable building pymomentum on Windows

.github/workflows/ci_windows.yml

@@ -13,8 +13,8 @@ on:
       - "**/website/**"
 
 jobs:
-  build:
-    name: win
+  momentum:
+    name: momentum-win
     runs-on: windows-latest
     steps:
       - name: Checkout
@@ -36,3 +36,17 @@ jobs:
             --build momentum/examples/hello_world/build `
             --config Release `
             --parallel
+
+  pymomentum:
+    name: pymomentum-win
+    runs-on: windows-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Set up pixi
+        uses: prefix-dev/setup-pixi@v0.8.1
+        with:
+          cache: true
+      - name: Build PyMomentum
+        run: |
+          pixi run test_pymomentum

pixi.toml

@@ -1,9 +1,12 @@
 [project]
 name = "momentum"
-channels = ["conda-forge"]
+channels = ["conda-forge", "pytorch"]
 platforms = ["linux-64", "osx-64", "osx-arm64", "win-64"]
 version = "0.1.0"
-description = "A library providing foundational algorithms for human kinematic motion and numerical optimization solvers to apply human motion in various applications"
+description = """
+A library providing foundational algorithms for human kinematic motion and numerical optimization \
+solvers to apply human motion in various applications
+"""
 license = "MIT"
 readme = "README.md"
 homepage = "https://facebookincubator.github.io/momentum/"
@@ -24,7 +27,6 @@ scipy = ">=1.13.0,<1.14"
 setuptools = ">=69.5.1,<69.6"
 
 [dependencies]
-blas = ">=1.1,<3"
 ceres-solver = ">=2.2.0,<2.3"
 cli11 = ">=2.4.1,<2.5"
 dispenso = ">=1.3.0,<1.4"
@@ -141,6 +143,8 @@ build_pymomentum = { cmd = "pip install -e ." }
 #=========
 
 [target.win-64.dependencies]
+mkl-static = ">=2018"                                       # Needed by pytorch::pytorch
+pytorch = { version = ">=2.4.1,<2.5", channel = "pytorch" } # TODO: Migrate to conda-forge::pytorch once available on Windows
 
 [target.win-64.tasks]
 configure = { cmd = """
@@ -156,18 +160,30 @@ configure = { cmd = """
         -DMOMENTUM_BUILD_TESTING=ON \
         -DMOMENTUM_ENABLE_SIMD=%MOMENTUM_ENABLE_SIMD% \
         -DMOMENTUM_USE_SYSTEM_GOOGLETEST=ON \
-        -DMOMENTUM_USE_SYSTEM_PYBIND11=ON \
+        -DMOMENTUM_USE_SYSTEM_PYBIND11=OFF \
         -DMOMENTUM_USE_SYSTEM_RERUN_CPP_SDK=ON
-    """, env = { MOMENTUM_ENABLE_SIMD = "ON", MOMENTUM_BUILD_PYMOMENTUM = "OFF" } }
+    """, env = { MOMENTUM_ENABLE_SIMD = "ON", MOMENTUM_BUILD_PYMOMENTUM = "ON" } }
 open_vs = { cmd = "cmd /c start build\\momentum.sln", depends_on = [
     "configure",
 ] }
 build = { cmd = "cmake --build build -j --config Release", depends_on = [
     "configure",
 ] }
+build_pymomentum = { cmd = "pip install -e ." }
 test = { cmd = "ctest --test-dir build --output-on-failure --build-config Release", depends_on = [
     "build",
 ] }
+test_pymomentum = { cmd = """
+    pytest \
+        pymomentum/test/test_closest_points.py \
+        pymomentum/test/test_fbx.py \
+        pymomentum/test/test_parameter_transform.py \
+        pymomentum/test/test_quaternion.py \
+        pymomentum/test/test_skel_state.py \
+        pymomentum/test/test_skeleton.py
+    """, env = { MOMENTUM_MODELS_PATH = "momentum/" }, depends_on = [
+    "build_pymomentum",
+] }
 hello_world = { cmd = "build/Release/hello_world.exe", depends_on = ["build"] }
 convert_model = { cmd = "build/Release/convert_model.exe", depends_on = [
     "build",

pymomentum/CMakeLists.txt

@@ -7,24 +7,20 @@
 # Find dependencies
 #===============================================================================
 
-set(ENV{NVTOOLSEXT_PATH} "$ENV{CONDA_PREFIX}/include")
-
-find_package(ATen CONFIG REQUIRED
-  HINTS
-    $ENV{CONDA_PREFIX}/lib/python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR}/site-packages/torch/
-)
-
-find_package(Torch CONFIG REQUIRED
-  HINTS
-    $ENV{CONDA_PREFIX}/lib/python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR}/site-packages/torch/
-)
+if(MSVC)
+  set(torch_lib_path "$ENV{CONDA_PREFIX}/lib/site-packages/torch/")
+  set(nvtoolsext_path "$ENV{CONDA_PREFIX}/include")
+  string(REPLACE "\\" "/" torch_lib_path ${torch_lib_path})
+  string(REPLACE "\\" "/" nvtoolsext_path ${nvtoolsext_path})
+else()
+  set(torch_lib_path "$ENV{CONDA_PREFIX}/lib/python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR}/site-packages/torch/")
+  set(nvtoolsext_path "$ENV{CONDA_PREFIX}/include")
+endif()
 
-find_library(torch_python
-  NAMES torch_python
-  HINTS
-    $ENV{CONDA_PREFIX}/lib/python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR}/site-packages/torch/lib/
-  REQUIRED
-)
+set(ENV{NVTOOLSEXT_PATH} "${nvtoolsext_path}")
+find_package(ATen CONFIG REQUIRED HINTS "${torch_lib_path}")
+find_package(Torch CONFIG REQUIRED HINTS "${torch_lib_path}")
+find_library(torch_python NAMES torch_python HINTS "${torch_lib_path}/lib" REQUIRED)
 
 #===============================================================================
 # Find build dependencies

pymomentum/geometry/momentum_geometry.cpp

@@ -444,7 +444,7 @@ at::Tensor uniformRandomToModelParameters(
 
   at::Tensor result = at::zeros({nBatch, nModelParam}, at::kFloat);
 
-  for (ssize_t iBatch = 0; iBatch < nBatch; ++iBatch) {
+  for (size_t iBatch = 0; iBatch < nBatch; ++iBatch) {
     auto res_i = toEigenMap<float>(result.select(0, iBatch));
     auto unif_i = toEigenMap<float>(unifNoise.select(0, iBatch));
 
@@ -1008,7 +1008,7 @@ std::tuple<MatrixX7f, MatrixX7f> jointParameterLimits(
 py::array_t<float> getBindPose(const momentum::Character& character) {
   const auto& inverseBindPose = character.inverseBindPose;
   py::array_t<float> result = py::array_t<float>(
-      std::vector<ssize_t>{(ssize_t)inverseBindPose.size(), 4, 4});
+      std::vector<size_t>{(size_t)inverseBindPose.size(), 4, 4});
   auto r = result.mutable_unchecked<3>(); // Will throw if ndim != 3 or
                                           // flags.writable is false
   for (py::ssize_t i = 0; i < inverseBindPose.size(); i++) {
@@ -1025,7 +1025,7 @@ py::array_t<float> getBindPose(const momentum::Character& character) {
 py::array_t<float> getInverseBindPose(const momentum::Character& character) {
   const auto& inverseBindPose = character.inverseBindPose;
   py::array_t<float> result = py::array_t<float>(
-      std::vector<ssize_t>{(ssize_t)inverseBindPose.size(), 4, 4});
+      std::vector<size_t>{(size_t)inverseBindPose.size(), 4, 4});
   auto r = result.mutable_unchecked<3>(); // Will throw if ndim != 3 or
                                           // flags.writable is false
   for (py::ssize_t i = 0; i < inverseBindPose.size(); i++) {

pymomentum/tensor_momentum/tensor_skeleton_state.cpp

@@ -112,8 +112,7 @@ void computeSkelStateBackward(
       for (int d = 0; d < momentum::kParametersPerJoint; ++d) {
         Eigen::VectorX<JetType> jointParams_cur =
             jointParameters
-                .template segment(
-                    kParametersPerJoint * curJoint, kParametersPerJoint)
+                .segment(kParametersPerJoint * curJoint, kParametersPerJoint)
                 .template cast<JetType>();
         jointParams_cur(d).v[0] = 1;
 
@@ -189,8 +188,7 @@ void computeLocalSkelStateBackward(
     for (int d = 0; d < momentum::kParametersPerJoint; ++d) {
       Eigen::VectorX<JetType> jointParams_cur =
           jointParameters
-              .template segment(
-                  kParametersPerJoint * iJoint, kParametersPerJoint)
+              .segment(kParametersPerJoint * iJoint, kParametersPerJoint)
               .template cast<JetType>();
       jointParams_cur(d).v[0] = 1;
 

pymomentum/tensor_utility/tensor_utility.cpp

@@ -32,7 +32,7 @@ std::string formatTensorSizes(const at::Tensor& tensor) {
   return formatTensorSizes(sizes.begin(), sizes.end());
 }
 
-std::string formatTensorSizes(const std::vector<ssize_t>& sizes) {
+std::string formatTensorSizes(const std::vector<size_t>& sizes) {
   return formatTensorSizes(sizes.begin(), sizes.end());
 }
 

pymomentum/tensor_utility/tensor_utility.h

@@ -33,7 +33,7 @@ template <typename T>
 Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, 1>> toEigenMap(at::Tensor t);
 
 std::string formatTensorSizes(const at::Tensor& tensor);
-std::string formatTensorSizes(const std::vector<ssize_t>& dims);
+std::string formatTensorSizes(const std::vector<size_t>& dims);
 
 inline bool isEmpty(const at::Tensor& t) {
   return (t.numel() == 0);