Use tensorflow 2.4.4 and GPU
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@ -1,12 +1,11 @@
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FROM nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 AS python-ubuntu
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FROM nvidia/cuda:11.2.0-cudnn8-runtime-ubuntu18.04 AS python-ubuntu
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RUN apt-get update
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RUN apt-get update
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RUN apt-get install -y build-essential curl python3 python3-pip python3-venv
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RUN apt-get install -y build-essential curl python3 python3-pip python3-venv
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# Inorder to run pip3.6, run it the following way `python3.6 -m pip`
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# Inorder to run pip3.6, run it the following way `python3.6 -m pip`
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# Update Python & Install wheel
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# Update Python & Install wheel
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RUN python3 -m pip install pip --upgrade
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RUN python3 -m pip install pip --upgrade && ython3 -m pip install wheel
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RUN python3 -m pip install wheel
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FROM python-ubuntu
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FROM python-ubuntu
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@ -15,7 +14,7 @@ RUN apt-get update && apt-get install -y \
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pkg-config portaudio19-dev swig libpulse-ocaml-dev gfortran \
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pkg-config portaudio19-dev swig libpulse-ocaml-dev gfortran \
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libopenblas-dev libatlas-base-dev
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libopenblas-dev libatlas-base-dev
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RUN mkdir /training && pip3 install precise-lite && pip3 install tensorflow-gpu==2.3.1
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RUN mkdir /training && pip3 install precise-lite && pip3 install tensorflow==2.4.4 && pip3 install tensorflow-gpu==2.4.4
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WORKDIR /training
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WORKDIR /training
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@ -2,4 +2,32 @@
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set -e
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set -e
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exec $@
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function populate_env() {
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if [[ -z "$MODEL_PATH" ] && [ ! -z "$1" ]]; then
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export MODEL_PATH="$1"
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fi
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if [[ -z "$DATA_FOLDER" ] && [ ! -z "$2" ]]; then
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export DATA_FOLDER="$2"
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fi
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}
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populate_env
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case "$1" in
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train)
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precise-lite-train $TRAIN_ARGS "$MODEL_PATH" "$DATA_FOLDER"
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;;
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"train-incremental")
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precise-lite-train-incremental $TRAIN_ARGS "$MODEL_PATH" "$DATA_FOLDER"
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;;
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test)
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precise-lite-test "$MODEL_PATH" "$DATA_FOLDER"
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;;
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convert)
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precise-lite-convert "$MODEL_PATH"
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;;
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*)
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exec $@
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;;
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esac
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