✨ Add run-docker-compatibility-matrix to test more combinations

run-docker

@@ -9,6 +9,6 @@ for tf in tf1 tf2; do
   esac
   work_dir=`dirname $0`
   image_id=`docker build -q --build-arg tf=$tf --build-arg BASE_IMAGE=$BASE_IMAGE -f assets/Dockerfile $work_dir`
-  docker run --gpus all -it --rm $image_id
+  docker run --gpus all -it --rm -e TF_CPP_MIN_LOG_LEVEL=1 $image_id
   docker rmi $image_id >/dev/null || true
 done

run-docker-compatibility-matrix

@@ -0,0 +1,18 @@
+#!/bin/sh
+set -e
+
+for tf in tf1 tf2; do
+  #  Note: CUDA 11.0 only with CUDNN 8
+  for BASE_IMAGE in \
+    nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 \
+    nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 \
+    nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04 \
+    nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04 \
+  ; do
+    echo "== $tf $BASE_IMAGE"
+    work_dir=`dirname $0`
+    image_id=`docker build -q --build-arg tf=$tf --build-arg BASE_IMAGE=$BASE_IMAGE -f assets/Dockerfile $work_dir`
+    docker run --gpus all -it --rm -e TF_CPP_MIN_LOG_LEVEL=2 $image_id
+    docker rmi $image_id >/dev/null || true
+  done
+done

test-nvidia

@@ -5,7 +5,8 @@ import os
 os.system('nvidia-smi -L')
 
 
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1'  # '1' means >= WARN
+if not 'TF_CPP_MIN_LOG_LEVEL' in os.environ:
+    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1'  # '1' means >= WARN
 import tensorflow as tf
 print('TensorFlow', tf.__version__)
 with tf.compat.v1.Session() as sess: