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Upgrade base image to m64. (#969)
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- Pin pyproj since 3.x is not compatible with latest version of basemap
yet.
- Improved the basemap test.

http:https://b/182405233
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rosbo committed Mar 11, 2021
1 parent 25beb81 commit 8bf4913
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Showing 3 changed files with 7 additions and 6 deletions.
7 changes: 4 additions & 3 deletions Dockerfile
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@@ -1,4 +1,4 @@
ARG BASE_TAG=m61
ARG BASE_TAG=m64
ARG TENSORFLOW_VERSION=2.4.1

FROM gcr.io/kaggle-images/python-tensorflow-whl:${TENSORFLOW_VERSION}-py37 as tensorflow_whl
Expand Down Expand Up @@ -39,8 +39,9 @@ RUN conda config --add channels conda-forge && \
conda config --add channels pytorch && \
conda config --add channels rapidsai && \
# ^ rapidsai is the highest priority channel, default lowest, conda-forge 2nd lowest.
# 161473620#comment7 pin required to prevent resolver from picking pysal 1.x., pysal 2.2.x is also downloading data on import.
conda install matplotlib basemap cartopy python-igraph imagemagick "pysal==2.1.0" && \
# b/182405233 pyproj 3.x is not compatible with basemap 1.2.1
# b/161473620#comment7 pin required to prevent resolver from picking pysal 1.x., pysal 2.2.x is also downloading data on import.
conda install matplotlib basemap cartopy python-igraph imagemagick "pyproj=2.6" "pysal==2.1.0" && \
conda install "pytorch=1.7" "torchvision=0.8" "torchaudio=0.7" "torchtext=0.8" cpuonly && \
/tmp/clean-layer.sh

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2 changes: 1 addition & 1 deletion tensorflow-whl/Dockerfile
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@@ -1,5 +1,5 @@
FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04 AS nvidia
FROM gcr.io/deeplearning-platform-release/base-cpu:m61
FROM gcr.io/deeplearning-platform-release/base-cpu:m64

# Avoid interactive configuration prompts/dialogs during apt-get.
ENV DEBIAN_FRONTEND=noninteractive
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4 changes: 2 additions & 2 deletions tests/test_matplotlib.py
Original file line number Diff line number Diff line change
Expand Up @@ -14,5 +14,5 @@ def test_plot(self):
self.assertTrue(os.path.isfile("plot1.png"))

def test_basemap(self):
Basemap(width=100,height=100,projection='aeqd',
lat_0=40,lon_0=-105)
m = Basemap(width=100,height=100,projection='aeqd', lat_0=40,lon_0=-105)
self.assertEqual(0, m.xmin)

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