add py2 deprecation message to estimators and models

Author: Chuyang Deng

src/sagemaker/chainer/estimator.py

@@ -90,6 +90,10 @@ def __init__(self, entry_point, use_mpi=None, num_processes=None, process_slots_
 
         super(Chainer, self).__init__(entry_point, source_dir, hyperparameters,
                                       image_name=image_name, **kwargs)
+
+        if py_version == 'py2':
+            logger.warning('chainer py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.use_mpi = use_mpi
         self.num_processes = num_processes

src/sagemaker/chainer/model.py

@@ -12,12 +12,16 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
+import logging
+
 import sagemaker
 from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
 from sagemaker.chainer.defaults import CHAINER_VERSION
 from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer
 
+logger = logging.getLogger('sagemaker')
+
 
 class ChainerPredictor(RealTimePredictor):
     """A RealTimePredictor for inference against Chainer Endpoints.
@@ -66,6 +70,9 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py3',
         """
         super(ChainerModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
                                            **kwargs)
+        if py_version == 'py2':
+            logger.warning('chainer py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.framework_version = framework_version
         self.model_server_workers = model_server_workers

src/sagemaker/mxnet/estimator.py

@@ -79,6 +79,10 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio
 
         super(MXNet, self).__init__(entry_point, source_dir, hyperparameters,
                                     image_name=image_name, **kwargs)
+
+        if py_version == 'py2':
+            logger.warning('mxnet py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self._configure_distribution(distributions)
 

src/sagemaker/mxnet/model.py

@@ -12,12 +12,16 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
+import logging
+
 import sagemaker
 from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
 from sagemaker.mxnet.defaults import MXNET_VERSION
 from sagemaker.predictor import RealTimePredictor, json_serializer, json_deserializer
 
+logger = logging.getLogger('sagemaker')
+
 
 class MXNetPredictor(RealTimePredictor):
     """A RealTimePredictor for inference against MXNet Endpoints.
@@ -66,6 +70,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py2',
         """
         super(MXNetModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
                                          **kwargs)
+
+        if py_version == 'py2':
+            logger.warning('chainer py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.framework_version = framework_version
         self.model_server_workers = model_server_workers

src/sagemaker/pytorch/estimator.py

@@ -74,6 +74,10 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio
         self.framework_version = framework_version or PYTORCH_VERSION
 
         super(PyTorch, self).__init__(entry_point, source_dir, hyperparameters, image_name=image_name, **kwargs)
+
+        if py_version == 'py2':
+            logger.warning('pytorch py2 container will be deprecated soon.')
+
         self.py_version = py_version
 
     def create_model(self, model_server_workers=None, role=None, vpc_config_override=VPC_CONFIG_DEFAULT):

src/sagemaker/pytorch/model.py

@@ -11,12 +11,17 @@
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
+
+import logging
+
 import sagemaker
 from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
 from sagemaker.pytorch.defaults import PYTORCH_VERSION, PYTHON_VERSION
 from sagemaker.predictor import RealTimePredictor, npy_serializer, numpy_deserializer
 
+logger = logging.getLogger('sagemaker')
+
 
 class PyTorchPredictor(RealTimePredictor):
     """A RealTimePredictor for inference against PyTorch Endpoints.
@@ -65,6 +70,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version=PYTHON_
             **kwargs: Keyword arguments passed to the ``FrameworkModel`` initializer.
         """
         super(PyTorchModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls, **kwargs)
+
+        if py_version == 'py2':
+            logger.warning('pytorch py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.framework_version = framework_version
         self.model_server_workers = model_server_workers

src/sagemaker/tensorflow/estimator.py

@@ -236,6 +236,10 @@ def __init__(self, training_steps=None, evaluation_steps=None, checkpoint_path=N
 
         super(TensorFlow, self).__init__(image_name=image_name, **kwargs)
         self.checkpoint_path = checkpoint_path
+
+        if py_version == 'py2':
+            LOGGER.warning('tensorflow py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.training_steps = training_steps
         self.evaluation_steps = evaluation_steps

src/sagemaker/tensorflow/model.py

@@ -12,13 +12,17 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
+import logging
+
 import sagemaker
 from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
 from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
 from sagemaker.predictor import RealTimePredictor
 from sagemaker.tensorflow.defaults import TF_VERSION
 from sagemaker.tensorflow.predictor import tf_json_serializer, tf_json_deserializer
 
+LOGGER = logging.getLogger('sagemaker')
+
 
 class TensorFlowPredictor(RealTimePredictor):
     """A ``RealTimePredictor`` for inference against TensorFlow endpoint.
@@ -67,6 +71,10 @@ def __init__(self, model_data, role, entry_point, image=None, py_version='py2',
         """
         super(TensorFlowModel, self).__init__(model_data, image, role, entry_point, predictor_cls=predictor_cls,
                                               **kwargs)
+
+        if py_version == 'py2':
+            LOGGER.warning('tensorflow py2 container will be deprecated soon.')
+
         self.py_version = py_version
         self.framework_version = framework_version
         self.model_server_workers = model_server_workers