feature: add support for SKLearn 0.23

Author: Kim

src/sagemaker/fw_utils.py

@@ -587,10 +587,18 @@ def empty_framework_version_warning(default_version, latest_version):
     """
     msgs = [EMPTY_FRAMEWORK_VERSION_WARNING.format(default_version)]
     if default_version != latest_version:
-        msgs.append(LATER_FRAMEWORK_VERSION_WARNING.format(latest=latest_version))
+        msgs.append(later_framework_version_warning(latest_version))
     return " ".join(msgs)
 
 
+def later_framework_version_warning(latest_version):
+    """
+    Args:
+        latest_version:
+    """
+    return LATER_FRAMEWORK_VERSION_WARNING.format(latest=latest_version)
+
+
 def warn_if_parameter_server_with_multi_gpu(training_instance_type, distributions):
     """Warn the user that training will not fully leverage all the GPU
     cores if parameter server is enabled and a multi-GPU instance is selected.

src/sagemaker/sklearn/defaults.py

@@ -15,6 +15,11 @@
 
 SKLEARN_NAME = "scikit-learn"
 
+# Default SKLearn version for when the framework version is not specified.
+# This is no longer updated so as to not break existing workflows.
 SKLEARN_VERSION = "0.20.0"
+SKLEARN_LATEST_VERSION = "0.23-1"
+SKLEARN_SUPPORTED_VERSIONS = [SKLEARN_VERSION, SKLEARN_LATEST_VERSION]
+
 
 LATEST_PY2_VERSION = "0.20.0"

src/sagemaker/sklearn/estimator.py

@@ -19,7 +19,8 @@
 from sagemaker.fw_registry import default_framework_uri
 from sagemaker.fw_utils import (
     framework_name_from_image,
-    empty_framework_version_warning,
+    get_unsupported_framework_version_error,
+    later_framework_version_warning,
     python_deprecation_warning,
 )
 from sagemaker.sklearn import defaults
@@ -127,11 +128,17 @@ def __init__(
 
         self.py_version = py_version
 
-        if framework_version is None:
-            logger.warning(
-                empty_framework_version_warning(defaults.SKLEARN_VERSION, defaults.SKLEARN_VERSION)
+        if framework_version in defaults.SKLEARN_SUPPORTED_VERSIONS:
+            self.framework_version = framework_version
+        else:
+            raise ValueError(
+                get_unsupported_framework_version_error(
+                    self.__framework_name__, framework_version, defaults.SKLEARN_SUPPORTED_VERSIONS
+                )
             )
-        self.framework_version = framework_version or defaults.SKLEARN_VERSION
+
+        if framework_version != defaults.SKLEARN_LATEST_VERSION:
+            logger.warning(later_framework_version_warning(defaults.SKLEARN_LATEST_VERSION))
 
         if image_name is None:
             image_tag = "{}-{}-{}".format(framework_version, "cpu", py_version)

tests/unit/test_sklearn.py

@@ -574,6 +574,35 @@ def test_estimator_py2_warning(warning, sagemaker_session):
     warning.assert_called_with(estimator.__framework_name__, defaults.LATEST_PY2_VERSION)
 
 
+@patch("sagemaker.sklearn.estimator.later_framework_version_warning")
+def test_estimator_later_framework_version_warning(warning, sagemaker_session):
+    estimator = SKLearn(
+        entry_point=SCRIPT_PATH,
+        role=ROLE,
+        sagemaker_session=sagemaker_session,
+        train_instance_count=INSTANCE_COUNT,
+        train_instance_type=INSTANCE_TYPE,
+    )
+
+    assert estimator.framework_version == defaults.SKLEARN_VERSION
+    warning.assert_called_with(defaults.SKLEARN_LATEST_VERSION)
+
+
+@patch("sagemaker.sklearn.estimator.get_unsupported_framework_version_error")
+def test_estimator_throws_error_for_unsupported_version(error, sagemaker_session):
+    with pytest.raises(ValueError):
+        estimator = SKLearn(
+            entry_point=SCRIPT_PATH,
+            role=ROLE,
+            sagemaker_session=sagemaker_session,
+            train_instance_count=INSTANCE_COUNT,
+            train_instance_type=INSTANCE_TYPE,
+            framework_version="foo",
+        )
+        assert estimator.framework_version not in defaults.SKLEARN_SUPPORTED_VERSIONS
+        error.assert_called_with(defaults.SKLEARN_NAME, "foo", defaults.SKLEARN_SUPPORT_VERSIONS)
+
+
 @patch("sagemaker.sklearn.model.python_deprecation_warning")
 def test_model_py2_warning(warning, sagemaker_session):
     source_dir = "s3://mybucket/source"