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feat: Bump python to 3.10 for gpu docker image, use nvidia/cuda (#3701)
* Update pytorch base image * Small corrections * Revert back to load_schema() call * reverted to import haystack for schema generation Co-authored-by: Mayank Jobanputra <mayankjobanputra@gmail.com>
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@ -3,6 +3,7 @@ ARG base_immage
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FROM $build_image AS build-image
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ARG DEBIAN_FRONTEND=noninteractive
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ARG haystack_version
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ARG haystack_extras
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@ -25,10 +26,11 @@ RUN git clone --depth=1 --branch=${haystack_version} https://github.com/deepset-
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WORKDIR /opt/haystack
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# Use a virtualenv we can copy over the next build stage
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RUN python -m venv --system-site-packages /opt/venv
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RUN python3 -m venv --system-site-packages /opt/venv
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ENV PATH="/opt/venv/bin:$PATH"
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RUN pip install --upgrade pip && \
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pip install --no-cache-dir -U torchaudio && \
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pip install --no-cache-dir .${haystack_extras} && \
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pip install --no-cache-dir ./rest_api
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@ -40,3 +42,8 @@ COPY --from=build-image /opt/pdftotext /usr/local/bin
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RUN apt-get update && apt-get install -y libfontconfig && rm -rf /var/lib/apt/lists/*
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ENV PATH="/opt/venv/bin:$PATH"
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# Importing Haystack will generate and persist the json schema, we do this here for two reasons:
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# - the schema will be already there when the container runs, saving the generation overhead when a container starts
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# - derived images don't need to write the schema and can run with lower user privileges
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RUN python3 -c "import haystack"
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@ -54,8 +54,10 @@ target "base-gpu" {
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dockerfile = "Dockerfile.base"
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tags = ["${IMAGE_NAME}:base-gpu-${IMAGE_TAG_SUFFIX}"]
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args = {
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build_image = "pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime"
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base_immage = "pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime"
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# pytorch/pytorch:1.13.1-cuda11.6 ships Python 3.10.8
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build_image = "pytorch/pytorch:1.13.1-cuda11.6-cudnn8-runtime"
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base_immage = "pytorch/pytorch:1.13.1-cuda11.6-cudnn8-runtime"
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haystack_version = "${HAYSTACK_VERSION}"
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haystack_extras = notequal("",HAYSTACK_EXTRAS) ? "${HAYSTACK_EXTRAS}" : "[docstores-gpu,crawler,preprocessing,ocr,onnx-gpu]"
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}
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