Update Dockerfile

Dockerfile

@@ -1,11 +1,11 @@
-# Use the NVIDIA CUDA runtime as a base image
+# Use the NVIDIA CUDA runtime as a base image for CUDA 11.8
 FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
 
 # Set environment variables
 ENV DEBIAN_FRONTEND=noninteractive
 
+# Create a user and set environment variables
 RUN useradd -m -u 1000 user
-
 USER user
 
 ENV HOME=/home/user \
@@ -25,7 +25,7 @@ ENV HOME=/home/user \
 # Set the working directory to the user's home directory
 WORKDIR $HOME/app
 
-# Install Conda and create the environment
+# Install system dependencies as root
 USER root
 RUN apt-get update && apt-get install -y \
     wget \
@@ -35,30 +35,32 @@ RUN apt-get update && apt-get install -y \
     gnupg \
     libgl1-mesa-glx \
     libglib2.0-0 \
-    && wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
-    && bash miniconda.sh -b -p /opt/conda \
-    && rm miniconda.sh \
-    && /opt/conda/bin/conda init bash \
-    && /opt/conda/bin/conda update -n base -c defaults conda \
-    && /opt/conda/bin/conda install -y -c conda-forge mamba \
-    && /opt/conda/bin/mamba install -c nvidia -c pytorch -c conda-forge -c defaults python=3.9 pytorch=2.5.1 torchvision=0.20.1 torchaudio=2.5.1 pytorch-cuda=11.8 timm scikit-learn matplotlib pandas \
-    && rm -rf /var/lib/apt/lists/*
+    python3.9 \
+    python3.9-distutils \
+    python3.9-dev \
+    && curl -sS https://bootstrap.pypa.io/get-pip.py | python3.9 \
+    && update-alternatives --install /usr/bin/python python /usr/bin/python3.9 1 \
+    && update-alternatives --install /usr/bin/pip pip /usr/local/bin/pip 1 \
+    && apt-get clean
 
-# Verify installation
-RUN /opt/conda/bin/conda --version
-RUN /opt/conda/bin/python --version
-RUN /opt/conda/bin/python -c "import torch; print(torch.__version__)"
+# Install CUDA 11.8 and cuDNN 9.3.0 directly from NVIDIA's repositories
+RUN curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub | gpg --batch --yes --dearmor -o /usr/share/keyrings/cuda-archive-keyring.gpg \
+    && echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /" > /etc/apt/sources.list.d/cuda.list \
+    && apt-get update && apt-get install -y \
+    libcudnn9=8.9.3.0-1+cuda11.8 \
+    libcudnn9-dev=8.9.3.0-1+cuda11.8 \
+    libcudnn9-doc=8.9.3.0-1+cuda11.8 \
+    && apt-get clean
 
-USER user
-# Create the environment and activate it
-RUN /opt/conda/bin/conda env create -f /home/user/app/environment.yaml
-RUN echo "conda activate gazelle" >> ~/.bashrc
+# Verify CUDA and cuDNN installation
+RUN dpkg-query -W libcudnn9
 
-# Install additional Python dependencies
+# Install Python dependencies
+USER user
 COPY . .
-RUN /opt/conda/bin/pip install --upgrade pip
-RUN /opt/conda/bin/pip install -r requirements.txt
-RUN /opt/conda/bin/pip install gradio
+RUN pip install --upgrade pip
+RUN pip install -r requirements.txt
+RUN pip install gradio
 
 USER root
 # Configure git to trust the directory
@@ -72,4 +74,4 @@ ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
 ENV CUDA_VISIBLE_DEVICES=0
 
 # Command to run your application
-CMD ["/opt/conda/bin/python", "app.py"]
+CMD ["python", "app.py"]