Update Dockerfile

Dockerfile

@@ -1,56 +1,52 @@
-# Use NVIDIA's official CUDA development image
-FROM nvidia/cuda:12.1.1-devel-ubuntu22.04
+# 1. Use the NVIDIA image for Ubuntu 24.04 (Noble)
+FROM nvidia/cuda:12.4.1-devel-ubuntu24.04
 
 # Prevent interactive prompts
 ENV DEBIAN_FRONTEND=noninteractive
 
-# Install Python 3.12 and system dependencies
+# 2. Install Python 3.12 and required system libraries
 RUN apt-get update && apt-get install -y \
-    software-properties-common \
-    && add-apt-repository ppa:deadsnakes/ppa \
-    && apt-get update && apt-get install -y \
     python3.12 \
     python3.12-venv \
     python3.12-dev \
+    python3-pip \
     git \
     wget \
     libgl1 \
     libglib2.0-0 \
     && rm -rf /var/lib/apt/lists/*
 
-# Set up user
+# 3. Fix the Ubuntu 24.04 user conflict (UID 1000)
+RUN userdel -r ubuntu || true
 RUN useradd -m -u 1000 user
 USER user
-ENV HOME=/home/user \
-    PATH=/home/user/venv/bin:$PATH \
-    PYTHONWARNINGS="ignore::SyntaxWarning"
 
-# Force compilation for Ada Lovelace (8.9) and include Ampere (8.0/8.6) just in case
-ENV TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9"
-# Point to CUDA installation
-ENV CUDA_HOME=/usr/local/cuda
-ENV PATH=${CUDA_HOME}/bin:${PATH}
-ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+# 4. Set environment for L40S (Compute 8.9) and C++ libraries
+ENV HOME=/home/user \
+    PATH=/home/user/venv/bin:/usr/local/cuda/bin:$PATH \
+    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
+    PYTHONWARNINGS="ignore::SyntaxWarning" \
+    TORCH_CUDA_ARCH_LIST="8.9" \
+    CUDA_HOME=/usr/local/cuda
 
 WORKDIR $HOME/app
 
-# Create virtual environment
+# 5. Set up Virtual Environment
 RUN python3.12 -m venv $HOME/venv
 
-# Install PyTorch FIRST with explicit CUDA 12.1 support
+# 6. Install PyTorch with CUDA 12.4 support
 RUN pip install --no-cache-dir --upgrade pip && \
-    pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+    pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
 
-# Copy requirements and install the rest
+# 7. Install Pixal3D requirements
 COPY --chown=user requirements.txt .
-
-# We use --no-build-isolation to ensure extensions use the PyTorch/CUDA we just installed
+# We use --no-build-isolation to ensure it uses the CUDA 12.4 we just set up
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy application files
+# 8. Copy application files
 COPY --chown=user . .
 
-# App settings
+# 9. App settings
 EXPOSE 7860
 ENV GRADIO_SERVER_NAME="0.0.0.0"
 ENV GRADIO_SERVER_PORT="7860"