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Browse files- Dockerfile +91 -0
Dockerfile
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| 1 |
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FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
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# Set environment variables
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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ENV HF_HOME=/app/.cache/huggingface
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ENV TRANSFORMERS_CACHE=/app/.cache/huggingface/transformers
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ENV MPLCONFIGDIR=/tmp/matplotlib
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# Force PyTorch to use the NCCl backend
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ENV PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:128
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# Create necessary directories with proper permissions
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RUN mkdir -p /app/.cache/huggingface/transformers && \
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mkdir -p /tmp/matplotlib && \
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mkdir -p /app/gradio_cached_examples && \
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chmod -R 777 /app && \
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chmod -R 777 /tmp/matplotlib
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# Install system dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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git \
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curl \
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ca-certificates \
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python3-pip \
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python3-dev \
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python3-setuptools \
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&& rm -rf /var/lib/apt/lists/*
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# Create a working directory
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WORKDIR /app
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# Add a script to check GPU status at startup
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RUN echo '#!/bin/bash \n\
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echo "Checking NVIDIA GPU status..." \n\
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if ! command -v nvidia-smi &> /dev/null; then \n\
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echo "WARNING: nvidia-smi command not found. NVIDIA driver might not be installed." \n\
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else \n\
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echo "NVIDIA driver found. Running nvidia-smi:" \n\
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nvidia-smi \n\
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fi \n\
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echo "Environment variables for GPU:" \n\
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echo "CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES}" \n\
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echo "NVIDIA_VISIBLE_DEVICES=${NVIDIA_VISIBLE_DEVICES}" \n\
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exec "$@"' > /entrypoint.sh && \
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chmod +x /entrypoint.sh
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# Copy requirements file
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COPY requirements.txt .
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# Upgrade pip and install dependencies in specific order to avoid conflicts
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RUN pip3 install --no-cache-dir --upgrade pip && \
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# Install torch and torchvision first with CUDA support
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pip3 install --no-cache-dir torch==2.0.1+cu118 torchvision==0.15.2+cu118 --extra-index-url https://download.pytorch.org/whl/cu118 && \
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# Install core dependencies
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pip3 install --no-cache-dir numpy==1.24.3 scipy==1.11.3 requests==2.31.0 && \
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# Install typing-extensions first to ensure proper version for other packages
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pip3 install --no-cache-dir typing-extensions==4.10.0 && \
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# Install huggingface dependencies
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pip3 install --no-cache-dir transformers==4.37.2 safetensors==0.4.1 huggingface_hub==0.19.4 && \
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# Install timm for vision models
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pip3 install --no-cache-dir timm==0.9.11 && \
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# Install nest-asyncio for handling nested event loops
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pip3 install --no-cache-dir nest-asyncio==1.5.8 && \
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# Install lmdeploy and its dependencies first
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pip3 install --no-cache-dir "accelerate==0.30.0" && \
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pip3 install --no-cache-dir "lmdeploy==0.5.3" && \
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# Install other acceleration libraries
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pip3 install --no-cache-dir bitsandbytes==0.41.3 && \
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# Install gradio
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pip3 install --no-cache-dir gradio==3.38.0 && \
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# Install any remaining requirements
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pip3 install --no-cache-dir packaging==23.2 pyyaml==6.0.1 tqdm==4.66.1 openai==1.6.1
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# Copy the application files
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COPY . .
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# Make sure the runtime directories exist and have proper permissions
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RUN mkdir -p gradio_cached_examples && \
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chmod -R 777 gradio_cached_examples && \
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mkdir -p .cache/huggingface/transformers && \
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chmod -R 777 .cache
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# Make port 7860 available for the app
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EXPOSE 7860
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# Use our entrypoint script to check GPU status before starting the app
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ENTRYPOINT ["/entrypoint.sh"]
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# Start the application
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CMD ["python3", "app_internvl2.py"]
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