Update Dockerfile

Dockerfile

@@ -1,4 +1,4 @@
-FROM pytorch/pytorch:2.1.0-cuda11.8-cudnn8-runtime
+FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
 
 ENV DEBIAN_FRONTEND=noninteractive
 ENV MKL_THREADING_LAYER=GNU
@@ -6,17 +6,24 @@ ENV MKL_THREADING_LAYER=GNU
 # Install dependencies
 RUN apt-get update && apt-get install -y \
     git wget libgl1-mesa-glx libglib2.0-0 ffmpeg libx264-dev pkg-config \
-    build-essential cmake g++ python3-dev software-properties-common \
-    wget gnupg2 libopenblas-dev && \
+    build-essential cmake g++ python3.9 python3.9-dev python3.9-venv \
+    software-properties-common wget gnupg2 libopenblas-dev && \
     rm -rf /var/lib/apt/lists/*
 
+# Ensure Python 3.9 is the default version
+RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 1 && \
+    update-alternatives --set python3 /usr/bin/python3.9
+
+# Install pip for Python 3.9
+RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.9
+
 # Add NVIDIA package repositories
 RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb && \
     dpkg -i cuda-keyring_1.0-1_all.deb && \
     apt-get update
 
 # Install CUDA Toolkit and cuDNN
-RUN apt-get install -y cuda-toolkit-11-8 libcudnn8 libcudnn8-dev
+RUN apt-get install -y cuda-toolkit-11-7 libcudnn8 libcudnn8-dev
 
 # Create a user
 RUN useradd -m -u 1000 user