Merge pull request #144 from aws/arm-buildspec

ARM Build Spec Fix

Author: amzn-choeric

ci/buildspec_arm.yml

@@ -30,10 +30,11 @@ phases:
     - pip install wheel setuptools
     - python setup.py bdist_wheel
     - docker build -t preprod-sklearn:$FRAMEWORK_VERSION-cpu-py3-arm64 -f docker/$FRAMEWORK_VERSION/final/Dockerfile_arm.cpu .
-    - echo Running tox...
+    - echo Running tests...
     - printf "FROM preprod-sklearn:$FRAMEWORK_VERSION-cpu-py3-arm64\nADD . /app\nWORKDIR /app\nRUN python3 -m pip install .[test]" > Dockerfile_arm.test
     - docker build -t test-sklearn -f Dockerfile_arm.test .
-    - docker run --rm -t test-sklearn sh -c 'tox -e ALL'
+    - docker run --rm -t test-sklearn sh -c 'pytest --cov=sagemaker_sklearn_container --cov-fail-under=60 test/unit'
+    - docker run --rm -t test-sklearn sh -c 'flake8 setup.py src test'
     - echo Running container tests...
     - pytest test/integration --docker-base-name preprod-sklearn --tag $FRAMEWORK_VERSION-cpu-py3-arm64 --py-version 3 --framework-version $FRAMEWORK_VERSION
     - docker tag preprod-sklearn:$FRAMEWORK_VERSION-cpu-py3-arm64 515193369038.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:$FRAMEWORK_VERSION-cpu-py3-arm64

docker/1.0-1/base/Dockerfile_arm.cpu

@@ -7,7 +7,7 @@ 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
+ARG PYARROW_VERSION=1.0.0
 ARG MLIO_VERSION=arch-agnostic
 
 # Install python and other scikit-learn runtime dependencies

docker/1.0-1/final/Dockerfile_arm.cpu

@@ -1,4 +1,4 @@
-FROM sklearn-base:1.0-1-arm-cpu-py3
+FROM sklearn-base:1.0-1-cpu-py3-arm64
 ENV SAGEMAKER_SKLEARN_VERSION 1.0-1
 
 LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
@@ -49,7 +49,7 @@ ENV SM_CHECKPOINT_CONFIG_FILE $SM_INPUT/config/checkpointconfig.json
 # Set SageMaker serving environment variables
 ENV SM_MODEL_DIR /opt/ml/model
 
-#EXPOSE 8080
+EXPOSE 8080
 ENV TEMP=/home/model-server/tmp
 
 # Required label for multi-model loading