Remove extra installs from Dockerfile
This commit is contained in:
Josh Meyer
parent
f062f75e17
commit
649bc53536
@ -40,6 +40,7 @@ RUN wget --no-check-certificate https://github.com/coqui-ai/STT/releases/downloa
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rm temp.tar.xz
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#FROM gcr.io/kaggle-gpu-images/python:v98
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FROM nvcr.io/nvidia/tensorflow:21.05-tf1-py3
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ENV DEBIAN_FRONTEND=noninteractive
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@ -97,7 +98,7 @@ RUN rm -rf ~/.local/share/stt
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##
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#
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# FROM gcr.io/kaggle-gpu-images/python:v98
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#FROM gcr.io/kaggle-gpu-images/python:v98
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RUN chsh -s /bin/bash
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ENV SHELL=/bin/bash
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@ -119,74 +120,22 @@ RUN apt-get update && apt-get install -y \
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supervisor \
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gettext-base \
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less \
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nodejs \
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npm \
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&& rm -rf /var/lib/apt/lists/*
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# install nvm
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# https://github.com/creationix/nvm#install-script
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RUN curl --silent -o- https://raw.githubusercontent.com/creationix/nvm/v0.33.11/install.sh | bash
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#ENV NVM_DIR /root/.nvm
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ENV NVM_DIR /usr/local/nvm
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ENV NODE_VERSION v12.20.1
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# install node and npm
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RUN source $NVM_DIR/nvm.sh \
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&& nvm install $NODE_VERSION \
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&& nvm alias default $NODE_VERSION \
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&& nvm use default
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# add node and npm to path so the commands are available
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ENV NODE_PATH $NVM_DIR/versions/node/$NODE_VERSION/bin
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ENV PATH $NODE_PATH:$PATH
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RUN pip install pip==20.3.4
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RUN pip install jupyterlab==2.2.9 ipywidgets==7.6.3
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RUN pip3 install jupyterlab ipywidgets
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RUN jupyter labextension install @jupyter-widgets/jupyterlab-manager
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RUN jupyter nbextension enable --py widgetsnbextension #enable ipywidgets
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RUN jupyter labextension install jupyterlab-plotly@4.14.3
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RUN jupyter labextension install jupyterlab-plotly
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#install xlrd python module
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RUN pip install pyradiomics
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RUN pip install xlrd==1.2.0
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RUN pip install zarr
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RUN pip install imbalanced-learn
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RUN pip install openpyxl
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RUN pip install efficientnet-pytorch
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RUN pip install monai
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RUN pip install prince
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RUN pip install vit-pytorch
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RUN pip install lifelines==0.25.11
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RUN pip install timm==0.3.2
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RUN pip install keras-retinanet==1.0.0
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RUN python -m pip install histomicstk --find-links https://girder.github.io/large_image_wheels
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RUN pip install luminoth ipympl pysurvival missingpy pyinform pingouin pyAgrum missingno autoimpute networkx community yellowbrick factor_analyzer hdbscan pyitlib
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RUN pip install eli5 dtreeviz gower batchgenerators mlinsights efficientnet-pytorch pretrainedmodels
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# Add R to Jupyter Kernel
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RUN conda install -y -c r r-irkernel
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#Install survival, sm, ggplot2, Hmisc, mixOmics (ce dernier est en repositoire Bioconductor)
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RUN conda install -y -c cran r-survival
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RUN conda install -y -c cran r-sm
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RUN conda install -y -c cran r-ggplot2
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RUN conda install -y -c cran r-hmisc
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RUN conda install -y -c cran r-mixomics
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RUN conda install -y -c cran r-caret
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RUN conda install -y -c cran r-survminer
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RUN conda install -y -c cran r-ggfortify
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RUN conda install -y -c cran r-wordcloud
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RUN conda install -y -c cran r-tm
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RUN conda install -y -c cran r-prioritylasso
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RUN conda install -y -c cran r-blockforest
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RUN conda install -y -c cran r-mice
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#### tensorflow 1
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# Create the environment:
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SHELL ["/bin/bash", "-c"]
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COPY tfenv.yml .
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RUN conda env create -f tfenv.yml
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SHELL ["conda", "run", "-n", "tf1", "/bin/bash", "-c"]
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RUN python -m ipykernel install --name=tensorflow1
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# #### tensorflow 1
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# # Create the environment:
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# SHELL ["/bin/bash", "-c"]
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# COPY tfenv.yml .
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# RUN conda env create -f tfenv.yml
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# SHELL ["conda", "run", "-n", "tf1", "/bin/bash", "-c"]
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# RUN python -m ipykernel install --name=tensorflow1
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EXPOSE 8080
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@ -1,97 +0,0 @@
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# This is a Dockerfile useful for training models with Coqui STT.
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# You can train "acoustic models" with audio + Tensorflow, and
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# you can create "scorers" with text + KenLM.
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FROM ubuntu:20.04 AS kenlm-build
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ENV DEBIAN_FRONTEND=noninteractive
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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build-essential cmake libboost-system-dev \
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libboost-thread-dev libboost-program-options-dev \
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libboost-test-dev libeigen3-dev zlib1g-dev \
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libbz2-dev liblzma-dev && \
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rm -rf /var/lib/apt/lists/*
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# Build KenLM to generate new scorers
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WORKDIR /code
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COPY kenlm /code/kenlm
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RUN cd /code/kenlm && \
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mkdir -p build && \
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cd build && \
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cmake .. && \
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make -j $(nproc) || \
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( echo "ERROR: Failed to build KenLM."; \
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echo "ERROR: Make sure you update the kenlm submodule on host before building this Dockerfile."; \
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echo "ERROR: $ cd STT; git submodule update --init kenlm"; \
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exit 1; )
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FROM ubuntu:20.04 AS wget-binaries
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ENV DEBIAN_FRONTEND=noninteractive
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RUN apt-get update && apt-get install -y --no-install-recommends wget unzip xz-utils
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# Tool to convert output graph for inference
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RUN wget --no-check-certificate https://github.com/coqui-ai/STT/releases/download/v0.9.3/convert_graphdef_memmapped_format.linux.amd64.zip -O temp.zip && \
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unzip temp.zip && \
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rm temp.zip
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RUN wget --no-check-certificate https://github.com/coqui-ai/STT/releases/download/v0.9.3/native_client.tf.Linux.tar.xz -O temp.tar.xz && \
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tar -xf temp.tar.xz && \
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rm temp.tar.xz
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FROM jupyter/tensorflow-notebook
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ENV DEBIAN_FRONTEND=noninteractive
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USER root
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# We need to purge python3-xdg because
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# it's breaking STT install later with
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# errors about setuptools
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#
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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git \
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wget \
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libopus0 \
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libopusfile0 \
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libsndfile1 \
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sox \
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libsox-fmt-mp3 && \
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apt-get purge -y python3-xdg && \
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rm -rf /var/lib/apt/lists/
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# Make sure pip and its dependencies are up-to-date
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RUN pip3 install --upgrade pip wheel setuptools
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RUN pip3 uninstall -y tensorflow && pip3 install -y 'tensorflow-gpu==1.15.4'
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WORKDIR /code
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COPY native_client /code/native_client
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COPY .git /code/.git
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COPY training/coqui_stt_training/VERSION /code/training/coqui_stt_training/VERSION
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COPY training/coqui_stt_training/GRAPH_VERSION /code/training/coqui_stt_training/GRAPH_VERSION
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# Build CTC decoder first, to avoid clashes on incompatible versions upgrades
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RUN cd native_client/ctcdecode && make NUM_PROCESSES=$(nproc) bindings
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RUN pip3 install --upgrade native_client/ctcdecode/dist/*.whl
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COPY setup.py /code/setup.py
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COPY VERSION /code/VERSION
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COPY training /code/training
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# Copy files from previous build stages
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RUN mkdir -p /code/kenlm/build/
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COPY --from=kenlm-build /code/kenlm/build/bin /code/kenlm/build/bin
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COPY --from=wget-binaries /convert_graphdef_memmapped_format /code/convert_graphdef_memmapped_format
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COPY --from=wget-binaries /generate_scorer_package /code/generate_scorer_package
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# Install STT
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# No need for the decoder since we did it earlier
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# TensorFlow GPU should already be installed on the base image,
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# and we don't want to break that
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RUN DS_NODECODER=y DS_NOTENSORFLOW=y pip3 install --upgrade -e .
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# Copy rest of the code and test training
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COPY . /code
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RUN ./bin/run-ldc93s1.sh && rm -rf ~/.local/share/stt
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