add buildspec.yml for codebuild (#4)

Author: jesterhazy

buildspec.yml

@@ -0,0 +1,22 @@
+version: 0.2
+
+phases:
+  pre_build:
+    commands:
+      - start-dockerd.sh
+
+      # fix permissions dropped by CodePipeline
+      - chmod +x ./scripts/*.sh
+      - chmod +x ./container/sagemaker/serve
+  build:
+    commands:
+      - tox -e flake8,pylint,jshint
+
+      # build images
+      - ./scripts/build.sh --version 1.11 --arch cpu
+      - ./scripts/build.sh --version 1.11 --arch gpu
+      - ./scripts/build.sh --version 1.12 --arch cpu
+      - ./scripts/build.sh --version 1.12 --arch gpu
+
+      # run tests
+      - tox -e py36

scripts/build.sh

@@ -8,6 +8,14 @@ source scripts/shared.sh
 
 parse_std_args "$@"
 
-docker build -f docker/$major_version/Dockerfile.$arch \
+echo "pulling previous image for layer cache... "
+$(aws ecr get-login --no-include-email --registry-id $aws_account) &>/dev/null || echo 'warning: ecr login failed'
+docker pull $aws_account.dkr.ecr.$aws_region.amazonaws.com/sagemaker-tensorflow-serving:$minor_version-$arch &>/dev/null || echo 'warning: pull failed'
+docker logout https://$aws_account.dkr.ecr.$aws_region.amazonaws.com &>/dev/null
+
+echo "building image... "
+docker build \
+    --cache-from $aws_account.dkr.ecr.$aws_region.amazonaws.com/sagemaker-tensorflow-serving:$minor_version-$arch \
+    -f docker/$major_version/Dockerfile.$arch \
     -t sagemaker-tensorflow-serving:$minor_version-$arch \
     -t sagemaker-tensorflow-serving:$major_version-$arch container

scripts/publish.sh

@@ -8,7 +8,6 @@ source scripts/shared.sh
 
 parse_std_args "$@"
 
-aws_account=$(get_aws_account)
 $(aws ecr get-login --no-include-email --registry-id $aws_account)
 docker tag sagemaker-tensorflow-serving:$minor_version-$arch $aws_account.dkr.ecr.$aws_region.amazonaws.com/sagemaker-tensorflow-serving:$minor_version-$arch
 docker tag sagemaker-tensorflow-serving:$minor_version-$arch $aws_account.dkr.ecr.$aws_region.amazonaws.com/sagemaker-tensorflow-serving:$major_version-$arch

scripts/shared.sh

@@ -17,7 +17,11 @@ function get_minor_version() {
 }
 
 function get_default_region() {
-    aws configure get region
+    if [ -n "${AWS_DEFAULT_REGION:-}" ]; then
+        echo "$AWS_DEFAULT_REGION"
+    else
+        aws configure get region
+    fi
 }
 
 function get_aws_account() {
@@ -29,6 +33,7 @@ function parse_std_args() {
     arch='cpu'
     major_version=$(get_latest_major_version)
     aws_region=$(get_default_region)
+    aws_account=$(get_aws_account)
 
     while [[ $# -gt 0 ]]; do
     key="$1"

test/integration/test_container.py

@@ -23,30 +23,46 @@
 BASE_URL = 'http://localhost:8080/invocations'
 
 
+@pytest.fixture(scope='session', autouse=True)
+def volume():
+    try:
+        model_dir = os.path.abspath('test/resources/models')
+        subprocess.check_call(
+            'docker volume create --name model_volume --opt type=none '
+            '--opt device={} --opt o=bind'.format(model_dir).split())
+        yield model_dir
+    finally:
+        subprocess.check_call('docker volume rm model_volume'.split())
+
+
 @pytest.fixture(scope='module', autouse=True, params=['1.11', '1.12'])
 def container(request):
-    model_dir = os.path.abspath('test/resources/models')
-    command = 'docker run --name sagemaker-tensorflow-serving-test -v {}:/opt/ml/model:ro -p 8080:8080'.format(
-        model_dir)
-    command += ' -e SAGEMAKER_TFS_DEFAULT_MODEL_NAME=half_plus_three'
-    command += ' -e SAGEMAKER_TFS_NGINX_LOGLEVEL=info'
-    command += ' -e SAGEMAKER_BIND_TO_PORT=8080'
-    command += ' -e SAGEMAKER_SAFE_PORT_RANGE=9000-9999'
-    command += ' sagemaker-tensorflow-serving:{}-cpu serve'.format(request.param)
-    proc = subprocess.Popen(command.split(), stdout=sys.stdout, stderr=subprocess.STDOUT)
-
-    attempts = 0
-    while attempts < 5:
-        time.sleep(3)
-        try:
-            requests.get('http://localhost:8080/ping')
-            break
-        except:
-            attempts += 1
-            pass
-
-    yield proc.pid
-    subprocess.check_call('docker rm -f sagemaker-tensorflow-serving-test'.split())
+    try:
+        command = (
+            'docker run --name sagemaker-tensorflow-serving-test -p 8080:8080'
+            ' --mount type=volume,source=model_volume,target=/opt/ml/model,readonly'
+            ' -e SAGEMAKER_TFS_DEFAULT_MODEL_NAME=half_plus_three'
+            ' -e SAGEMAKER_TFS_NGINX_LOGLEVEL=info'
+            ' -e SAGEMAKER_BIND_TO_PORT=8080'
+            ' -e SAGEMAKER_SAFE_PORT_RANGE=9000-9999'
+            ' sagemaker-tensorflow-serving:{}-cpu serve'
+        ).format(request.param)
+
+        proc = subprocess.Popen(command.split(), stdout=sys.stdout, stderr=subprocess.STDOUT)
+
+        attempts = 0
+        while attempts < 5:
+            time.sleep(3)
+            try:
+                requests.get('http://localhost:8080/ping')
+                break
+            except:
+                attempts += 1
+                pass
+
+        yield proc.pid
+    finally:
+        subprocess.check_call('docker rm -f sagemaker-tensorflow-serving-test'.split())
 
 
 def make_request(data, content_type='application/json', method='predict'):
@@ -94,6 +110,7 @@ def test_predict_jsons():
     y = make_request(x, 'application/jsons')
     assert y == {'predictions': [[3.5, 4.0, 5.5], [3.5, 4.0, 5.5]]}
 
+
 def test_predict_jsons_2():
     x = '{"x": [1.0, 2.0, 5.0]}\n{"x": [1.0, 2.0, 5.0]}'
     y = make_request(x)