Build gsplat wheel directly in Docker for GPU architecture compatibility

- Build gsplat wheel in Docker with target GPU architectures (6.0-9.0)
- Install PyTorch first, then compile gsplat for the specific environment
- Set TORCH_CUDA_ARCH_LIST for broad GPU compatibility in HF Spaces
- This fixes 'no kernel image is available for execution on the device' error
- Ensures CUDA kernels match the actual GPU hardware available

Dockerfile

@@ -45,15 +45,28 @@ ENV HOME=/home/user \
 # Copy Docker-specific dependency files
 COPY --chown=user pyproject.docker.toml ./pyproject.toml
 
-# Download pre-built gsplat wheel from models repository
-RUN mkdir -p wheels && \
-    wget -O wheels/gsplat-0.1.0-cp310-cp310-linux_x86_64.whl \
-    "https://huggingface.co/blanchon/image-gs-models-utils/resolve/main/gsplat-0.1.0-cp310-cp310-linux_x86_64.whl"
+# Set CUDA compilation flags for HF Spaces GPU compatibility
+ENV TORCH_CUDA_ARCH_LIST="6.0;6.1;7.0;7.5;8.0;8.6;8.9;9.0" \
+    FORCE_CUDA=1
 
-# Create virtual environment and install dependencies
+# Create virtual environment first
+RUN uv venv .venv
+
+# Install PyTorch and basic dependencies first (needed for gsplat compilation)
+RUN --mount=type=cache,target=/tmp/uv-cache,sharing=locked,uid=1000,gid=1000 \
+    UV_CACHE_DIR=/tmp/uv-cache .venv/bin/pip install torch torchvision numpy
+
+# Copy gsplat source and build wheel for target architecture
+COPY --chown=user gsplat/ ./gsplat/
+RUN cd gsplat && \
+    ../.venv/bin/python setup.py bdist_wheel && \
+    mkdir -p ../wheels && \
+    cp dist/*.whl ../wheels/ && \
+    cd ..
+
+# Install all remaining dependencies with the fresh-built wheel
 RUN --mount=type=cache,target=/tmp/uv-cache,sharing=locked,uid=1000,gid=1000 \
-    UV_CACHE_DIR=/tmp/uv-cache uv sync --no-dev && \
-    uv venv .venv
+    UV_CACHE_DIR=/tmp/uv-cache uv sync --no-dev
 
 # Copy the rest of the application
 COPY --chown=user . .

pyproject.docker.toml

@@ -24,7 +24,7 @@ dependencies = [
 # We use python 3.10 and cu124
 [tool.uv.sources]
 fused_ssim = { git = "https://github.com/rahul-goel/fused-ssim/" }
-gsplat = { path = "wheels/gsplat-0.1.0-cp310-cp310-linux_x86_64.whl" }
+gsplat = { path = "gsplat" }
 torch = [
     { index = "pytorch-cu124", marker = "sys_platform == 'linux'" },
 ]