DockerfileSmartTag

FROM python:3.7-slim-buster AS base-compile-image

# amd64 or arm64, for example
ARG TARGETARCH

RUN apt-get update

# Set up the virtualenv that is copied to the build-image
RUN python -m venv /opt/venv
# Make sure we use the virtualenv:
ENV PATH="/opt/venv/bin:$PATH"

RUN pip install --upgrade pip

RUN pip install torch==1.10
RUN pip install python-dotenv==0.15.0


# The normal tensorflow package doesn't run on ARM, we need a special version for that.
# The blocks below acts basically like an if-else statement:
# if (ARM)   install tensorflow-aarch64
# elif (x86) install tensorflow
# else       fail
FROM base-compile-image AS compile-image-arm64
ENV TENSORFLOW_PACKAGE=tensorflow-aarch64==2.8.0

# Install a rust compiler, which is required to build the tokenizers package from source on the arm64 arch.
# tokenizers is a dependency of transformers, which we're installing below.
RUN apt-get install curl build-essential -y
RUN curl -sSf https://sh.rustup.rs | sh -s -- -y
ENV PATH="/root/.cargo/bin:${PATH}"


FROM base-compile-image AS compile-image-amd64
ENV TENSORFLOW_PACKAGE=tensorflow==2.4.0


FROM compile-image-${TARGETARCH} AS compile-image
RUN pip install transformers==4.15.0
RUN  pip install ${TENSORFLOW_PACKAGE}


FROM python:3.7-slim-buster AS build-image

COPY --from=compile-image /opt/venv /opt/venv
# Make sure we use the virtualenv:
ENV PATH="/opt/venv/bin:$PATH"

WORKDIR /app
RUN mkdir /app/smtag

COPY ./pipeline.py /app/smtag/pipeline.py
COPY ./xml2labels.py /app/smtag/xml2labels.py
COPY ./cli/inference/tag.py /app/smtag/cli/inference/tag.py
COPY ./__init__.py /app/smtag/__init__.py
COPY ./cli/__init__.py /app/smtag/cli/__init__.py
COPY ./cli/inference/__init__.py /app/smtag/cli/inference/__init__.py