upgrading sklearn to 1.0.2

Author: Nikhil Raverkar

docker/1.0-1/base/Dockerfile.cpu

@@ -3,8 +3,8 @@ ARG UBUNTU_IMAGE_DIGEST=98706f0f213dbd440021993a82d2f70451a73698315370ae8615cc46
 
 FROM ubuntu:${UBUNTU_VERSION}@sha256:${UBUNTU_IMAGE_DIGEST}
 
-ARG MINICONDA_VERSION=4.8.3
-ARG CONDA_PY_VERSION=37
+ARG MINICONDA_VERSION=4.11.0
+ARG CONDA_PY_VERSION=39
 ARG CONDA_PKG_VERSION=4.9.0
 ARG PYTHON_VERSION=3.7.10
 ARG PYARROW_VERSION=0.16.0

test/integration/test_multiple_model_endpoint.py

@@ -28,7 +28,6 @@
 path = os.path.abspath(__file__)
 resource_path = os.path.join(os.path.dirname(path), '..', 'resources')
 
-
 @pytest.fixture(scope='session', autouse=True)
 def volume():
     try:
@@ -56,18 +55,22 @@ def modulevolume():
 @pytest.fixture(scope='module', autouse=True)
 def container(request, docker_base_name, tag):
     test_name = 'sagemaker-sklearn-serving-test'
+    module_dir = os.path.join(resource_path, 'module')
+    model_dir = os.path.join(resource_path, 'models')
     try:
         command = (
             'docker run --name {} -p 8080:8080'
-            ' --mount type=volume,source=dynamic_endpoint_model_volume,target=/opt/ml/model,readonly'
+            #' --mount type=volume,source=dynamic_endpoint_model_volume,target=/opt/ml/model,readonly'
             ' --mount type=volume,source=dynamic_endpoint_module_volume,target=/user_module,readonly'
+            ' -v {}:/opt/ml/model'
+            ' -v {}:/user_module2'
             ' -e SAGEMAKER_BIND_TO_PORT=8080'
             ' -e SAGEMAKER_SAFE_PORT_RANGE=9000-9999'
             ' -e SAGEMAKER_MULTI_MODEL=true'
             ' -e SAGEMAKER_PROGRAM={}'
             ' -e SAGEMAKER_SUBMIT_DIRECTORY={}'
             ' {}:{} serve'
-        ).format(test_name, 'script.py', "/user_module/user_code.tar.gz", docker_base_name, tag)
+        ).format(test_name, model_dir, module_dir, 'script.py', "/user_module2/user_code.tar.gz", docker_base_name, tag)
 
         proc = subprocess.Popen(command.split(), stdout=sys.stdout, stderr=subprocess.STDOUT)