Upgrade base image to m64.

Dockerfile

@@ -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
@@ -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
 

tensorflow-whl/Dockerfile

@@ -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

tests/test_matplotlib.py

@@ -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)