fix: update py2 warning message since python 2 is deprecated

src/sagemaker/chainer/defaults.py

@@ -20,3 +20,5 @@
 
 LATEST_VERSION = "5.0.0"
 """The latest version of Chainer included in the SageMaker pre-built Docker images."""
+
+LATEST_PY2_VERSION = "5.0.0"

src/sagemaker/chainer/estimator.py

@@ -22,7 +22,7 @@
     empty_framework_version_warning,
     python_deprecation_warning,
 )
-from sagemaker.chainer.defaults import CHAINER_VERSION, LATEST_VERSION
+from sagemaker.chainer import defaults
 from sagemaker.chainer.model import ChainerModel
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
@@ -40,7 +40,7 @@ class Chainer(Framework):
     _process_slots_per_host = "sagemaker_process_slots_per_host"
     _additional_mpi_options = "sagemaker_additional_mpi_options"
 
-    LATEST_VERSION = LATEST_VERSION
+    LATEST_VERSION = defaults.LATEST_VERSION
 
     def __init__(
         self,
@@ -126,15 +126,19 @@ def __init__(
             :class:`~sagemaker.estimator.EstimatorBase`.
         """
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(CHAINER_VERSION, self.LATEST_VERSION))
-        self.framework_version = framework_version or CHAINER_VERSION
+            logger.warning(
+                empty_framework_version_warning(defaults.CHAINER_VERSION, self.LATEST_VERSION)
+            )
+        self.framework_version = framework_version or defaults.CHAINER_VERSION
 
         super(Chainer, self).__init__(
             entry_point, source_dir, hyperparameters, image_name=image_name, **kwargs
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
 
         self.py_version = py_version
         self.use_mpi = use_mpi

src/sagemaker/chainer/model.py

@@ -23,7 +23,7 @@
     empty_framework_version_warning,
 )
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
-from sagemaker.chainer.defaults import CHAINER_VERSION, LATEST_VERSION
+from sagemaker.chainer import defaults
 from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer
 
 logger = logging.getLogger("sagemaker")
@@ -111,12 +111,17 @@ def __init__(
             model_data, image, role, entry_point, predictor_cls=predictor_cls, **kwargs
         )
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
+
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(CHAINER_VERSION, LATEST_VERSION))
+            logger.warning(
+                empty_framework_version_warning(defaults.CHAINER_VERSION, defaults.LATEST_VERSION)
+            )
 
         self.py_version = py_version
-        self.framework_version = framework_version or CHAINER_VERSION
+        self.framework_version = framework_version or defaults.CHAINER_VERSION
         self.model_server_workers = model_server_workers
 
     def prepare_container_def(self, instance_type, accelerator_type=None):

src/sagemaker/fw_utils.py

@@ -38,8 +38,8 @@
     "please add framework_version={latest} to your constructor."
 )
 PYTHON_2_DEPRECATION_WARNING = (
-    "The Python 2 {framework} images will be soon deprecated and may not be "
-    "supported for newer upcoming versions of the {framework} images.\n"
+    "{latest_supported_version} is the latest version of {framework} that supports "
+    "Python 2. Newer versions of {framework} will only be available for Python 3."
     "Please set the argument \"py_version='py3'\" to use the Python 3 {framework} image."
 )
 
@@ -495,9 +495,12 @@ def get_unsupported_framework_version_error(
     )
 
 
-def python_deprecation_warning(framework):
+def python_deprecation_warning(framework, latest_supported_version):
     """
     Args:
         framework:
+        latest_supported_version:
     """
-    return PYTHON_2_DEPRECATION_WARNING.format(framework=framework)
+    return PYTHON_2_DEPRECATION_WARNING.format(
+        framework=framework, latest_supported_version=latest_supported_version
+    )

src/sagemaker/mxnet/defaults.py

@@ -20,3 +20,5 @@
 
 LATEST_VERSION = "1.6.0"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""
+
+LATEST_PY2_VERSION = "1.6.0"

src/sagemaker/mxnet/estimator.py

@@ -23,7 +23,7 @@
     python_deprecation_warning,
     is_version_equal_or_higher,
 )
-from sagemaker.mxnet.defaults import MXNET_VERSION, LATEST_VERSION
+from sagemaker.mxnet import defaults
 from sagemaker.mxnet.model import MXNetModel
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
@@ -36,7 +36,7 @@ class MXNet(Framework):
     __framework_name__ = "mxnet"
     _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]
 
-    LATEST_VERSION = LATEST_VERSION
+    LATEST_VERSION = defaults.LATEST_VERSION
 
     def __init__(
         self,
@@ -107,8 +107,10 @@ def __init__(
             :class:`~sagemaker.estimator.EstimatorBase`.
         """
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(MXNET_VERSION, self.LATEST_VERSION))
-        self.framework_version = framework_version or MXNET_VERSION
+            logger.warning(
+                empty_framework_version_warning(defaults.MXNET_VERSION, self.LATEST_VERSION)
+            )
+        self.framework_version = framework_version or defaults.MXNET_VERSION
 
         if "enable_sagemaker_metrics" not in kwargs:
             # enable sagemaker metrics for MXNet v1.6 or greater:
@@ -120,7 +122,9 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
 
         self.py_version = py_version
         self._configure_distribution(distributions)

src/sagemaker/mxnet/model.py

@@ -25,7 +25,7 @@
     empty_framework_version_warning,
 )
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
-from sagemaker.mxnet.defaults import MXNET_VERSION, LATEST_VERSION
+from sagemaker.mxnet import defaults
 from sagemaker.predictor import RealTimePredictor, json_serializer, json_deserializer
 
 logger = logging.getLogger("sagemaker")
@@ -113,12 +113,17 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
+
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(MXNET_VERSION, LATEST_VERSION))
+            logger.warning(
+                empty_framework_version_warning(defaults.MXNET_VERSION, defaults.LATEST_VERSION)
+            )
 
         self.py_version = py_version
-        self.framework_version = framework_version or MXNET_VERSION
+        self.framework_version = framework_version or defaults.MXNET_VERSION
         self.model_server_workers = model_server_workers
 
     def prepare_container_def(self, instance_type, accelerator_type=None):

src/sagemaker/pytorch/defaults.py

@@ -23,3 +23,5 @@
 """The latest version of PyTorch included in the SageMaker pre-built Docker images."""
 
 PYTHON_VERSION = "py3"
+
+LATEST_PY2_VERSION = "1.3.1"

src/sagemaker/pytorch/estimator.py

@@ -23,7 +23,7 @@
     python_deprecation_warning,
     is_version_equal_or_higher,
 )
-from sagemaker.pytorch.defaults import PYTORCH_VERSION, PYTHON_VERSION, LATEST_VERSION
+from sagemaker.pytorch import defaults
 from sagemaker.pytorch.model import PyTorchModel
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
@@ -35,14 +35,14 @@ class PyTorch(Framework):
 
     __framework_name__ = "pytorch"
 
-    LATEST_VERSION = LATEST_VERSION
+    LATEST_VERSION = defaults.LATEST_VERSION
 
     def __init__(
         self,
         entry_point,
         source_dir=None,
         hyperparameters=None,
-        py_version=PYTHON_VERSION,
+        py_version=defaults.PYTHON_VERSION,
         framework_version=None,
         image_name=None,
         **kwargs
@@ -103,8 +103,10 @@ def __init__(
             :class:`~sagemaker.estimator.EstimatorBase`.
         """
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(PYTORCH_VERSION, self.LATEST_VERSION))
-        self.framework_version = framework_version or PYTORCH_VERSION
+            logger.warning(
+                empty_framework_version_warning(defaults.PYTORCH_VERSION, self.LATEST_VERSION)
+            )
+        self.framework_version = framework_version or defaults.PYTORCH_VERSION
 
         if "enable_sagemaker_metrics" not in kwargs:
             # enable sagemaker metrics for PT v1.3 or greater:
@@ -116,7 +118,9 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
 
         self.py_version = py_version
 

src/sagemaker/pytorch/model.py

@@ -24,7 +24,7 @@
     empty_framework_version_warning,
 )
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
-from sagemaker.pytorch.defaults import PYTORCH_VERSION, PYTHON_VERSION, LATEST_VERSION
+from sagemaker.pytorch import defaults
 from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer
 
 logger = logging.getLogger("sagemaker")
@@ -67,7 +67,7 @@ def __init__(
         role,
         entry_point,
         image=None,
-        py_version=PYTHON_VERSION,
+        py_version=defaults.PYTHON_VERSION,
         framework_version=None,
         predictor_cls=PyTorchPredictor,
         model_server_workers=None,
@@ -114,12 +114,17 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
+
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(PYTORCH_VERSION, LATEST_VERSION))
+            logger.warning(
+                empty_framework_version_warning(defaults.PYTORCH_VERSION, defaults.LATEST_VERSION)
+            )
 
         self.py_version = py_version
-        self.framework_version = framework_version or PYTORCH_VERSION
+        self.framework_version = framework_version or defaults.PYTORCH_VERSION
         self.model_server_workers = model_server_workers
 
     def prepare_container_def(self, instance_type, accelerator_type=None):

src/sagemaker/sklearn/defaults.py

@@ -16,3 +16,5 @@
 SKLEARN_NAME = "scikit-learn"
 
 SKLEARN_VERSION = "0.20.0"
+
+LATEST_PY2_VERSION = "0.20.0"

src/sagemaker/sklearn/estimator.py

@@ -22,7 +22,7 @@
     empty_framework_version_warning,
     python_deprecation_warning,
 )
-from sagemaker.sklearn.defaults import SKLEARN_VERSION, SKLEARN_NAME
+from sagemaker.sklearn import defaults
 from sagemaker.sklearn.model import SKLearnModel
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
@@ -32,12 +32,12 @@
 class SKLearn(Framework):
     """Handle end-to-end training and deployment of custom Scikit-learn code."""
 
-    __framework_name__ = SKLEARN_NAME
+    __framework_name__ = defaults.SKLEARN_NAME
 
     def __init__(
         self,
         entry_point,
-        framework_version=SKLEARN_VERSION,
+        framework_version=defaults.SKLEARN_VERSION,
         source_dir=None,
         hyperparameters=None,
         py_version="py3",
@@ -119,13 +119,17 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
 
         self.py_version = py_version
 
         if framework_version is None:
-            logger.warning(empty_framework_version_warning(SKLEARN_VERSION, SKLEARN_VERSION))
-        self.framework_version = framework_version or SKLEARN_VERSION
+            logger.warning(
+                empty_framework_version_warning(defaults.SKLEARN_VERSION, defaults.SKLEARN_VERSION)
+            )
+        self.framework_version = framework_version or defaults.SKLEARN_VERSION
 
         if image_name is None:
             image_tag = "{}-{}-{}".format(framework_version, "cpu", py_version)

src/sagemaker/sklearn/model.py

@@ -20,7 +20,7 @@
 from sagemaker.fw_registry import default_framework_uri
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
 from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer
-from sagemaker.sklearn.defaults import SKLEARN_VERSION, SKLEARN_NAME
+from sagemaker.sklearn import defaults
 
 logger = logging.getLogger("sagemaker")
 
@@ -53,7 +53,7 @@ class SKLearnModel(FrameworkModel):
     ``Endpoint``.
     """
 
-    __framework_name__ = SKLEARN_NAME
+    __framework_name__ = defaults.SKLEARN_NAME
 
     def __init__(
         self,
@@ -62,7 +62,7 @@ def __init__(
         entry_point,
         image=None,
         py_version="py3",
-        framework_version=SKLEARN_VERSION,
+        framework_version=defaults.SKLEARN_VERSION,
         predictor_cls=SKLearnPredictor,
         model_server_workers=None,
         **kwargs
@@ -108,7 +108,9 @@ def __init__(
         )
 
         if py_version == "py2":
-            logger.warning(python_deprecation_warning(self.__framework_name__))
+            logger.warning(
+                python_deprecation_warning(self.__framework_name__, defaults.LATEST_PY2_VERSION)
+            )
 
         self.py_version = py_version
         self.framework_version = framework_version

src/sagemaker/tensorflow/defaults.py

@@ -20,3 +20,5 @@
 
 LATEST_VERSION = "2.0.0"
 """The latest version of TensorFlow included in the SageMaker pre-built Docker images."""
+
+LATEST_PY2_VERSION = "2.0.0"