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Numpy Installation Issue & ARM Dockerfile PyArrow Update #162

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Merged
merged 1 commit into from
Feb 10, 2023
Merged

Numpy Installation Issue & ARM Dockerfile PyArrow Update #162

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2 changes: 0 additions & 2 deletions docker/1.0-1/base/Dockerfile.cpu
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Expand Up @@ -10,7 +10,6 @@ ARG CONDA_PKG_VERSION=4.13.0
ARG PYTHON_VERSION=3.8.13
ARG PYARROW_VERSION=10.0.1
ARG MLIO_VERSION=v0.8.0
ARG NUMPY_VERSION=1.24.1

# Install python and other scikit-learn runtime dependencies
# Dependency list from http://scikit-learn.org/stable/developers/advanced_installation.html#installing-build-dependencies
Expand Down Expand Up @@ -82,7 +81,6 @@ RUN echo "conda ${CONDA_PKG_VERSION}" >> /miniconda3/conda-meta/pinned && \
conda install -c conda-forge python=${PYTHON_VERSION} && \
conda install conda=${CONDA_PKG_VERSION} && \
conda update -y conda && \
conda install -c conda-forge numpy=${NUMPY_VERSION} && \
conda install -c conda-forge pyarrow=${PYARROW_VERSION} && \
cd /tmp && \
git clone --branch ${MLIO_VERSION} https://github.com/awslabs/ml-io.git mlio && \
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8 changes: 6 additions & 2 deletions docker/1.0-1/base/Dockerfile_arm.cpu
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Expand Up @@ -7,8 +7,8 @@ ARG MINICONDA_VERSION=4.9.2 # Upgraded version
ARG CONDA_PY_VERSION=38
ARG CONDA_PKG_VERSION=4.10.1
ARG PYTHON_VERSION=3.8.13
ARG PYARROW_VERSION=1.0.0
ARG MLIO_VERSION=arch-agnostic
ARG PYARROW_VERSION=10.0.1
ARG MLIO_VERSION=0.8.0

# Install python and other scikit-learn runtime dependencies
# Dependency list from http://scikit-learn.org/stable/developers/advanced_installation.html#installing-build-dependencies
Expand Down Expand Up @@ -66,6 +66,10 @@ RUN apt-get update && \
rm /etc/apt/trusted.gpg.d/kitware.gpg && \
rm -rf /var/lib/apt/lists/*

# http://ftp.us.debian.org/debian/pool/main/libf/libffi/libffi7_3.3-6_arm64.deb
COPY docker/1.0-1/resources/libffi7_3.3-6_arm64.deb /tmp
RUN dpkg -i /tmp/libffi7_3.3-6_arm64.deb

RUN cd /tmp && \
curl -L --output /tmp/Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-py${CONDA_PY_VERSION}_${MINICONDA_VERSION}-Linux-aarch64.sh && \
bash /tmp/Miniconda3.sh -bfp /miniconda3 && \
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6 changes: 3 additions & 3 deletions docker/1.0-1/final/Dockerfile.cpu
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Expand Up @@ -8,9 +8,9 @@ RUN python -m pip install -r /requirements.txt && \
rm /requirements.txt

COPY dist/sagemaker_sklearn_container-2.0-py3-none-any.whl /sagemaker_sklearn_container-2.0-py3-none-any.whl
# https://github.com/googleapis/google-cloud-python/issues/6647
RUN rm -rf /miniconda3/lib/python3.7/site-packages/numpy-1.19.4.dist-info && \
pip install --no-cache /sagemaker_sklearn_container-2.0-py3-none-any.whl && \
RUN rm /miniconda3/lib/python3.8/site-packages/**/REQUESTED && \
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Should we use -f here in case the file doesn't exist going forward?

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I think it is fine if we leave it as is. These files are part of the PyPA specs, and reasons for why these files may no longer exist would relate to us not using conda or not having a requirements file. Even if in that unlikely scenario, I think it is fine for this to fail at build time on our side to force us to remove this.

rm /miniconda3/lib/python3.8/site-packages/**/direct_url.json
RUN pip install --no-cache /sagemaker_sklearn_container-2.0-py3-none-any.whl && \
rm /sagemaker_sklearn_container-2.0-py3-none-any.whl

ENV SAGEMAKER_TRAINING_MODULE sagemaker_sklearn_container.training:main
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1 change: 1 addition & 0 deletions requirements.txt
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Expand Up @@ -22,3 +22,4 @@ MarkupSafe==2.1.1
Werkzeug==0.15.6
setuptools==65.5.1
wheel==0.38.1
numpy==1.24.1