add newline to warning message

Author: Dan Choi

src/sagemaker/fw_utils.py

@@ -37,7 +37,7 @@
                                   'If you would like to use version {latest}, ' \
                                   '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. ' \
+                               'supported for newer upcoming versions of the {framework} images.\n' \
                                'Please set the argument \"py_version=\'py3\'\" to use the Python 3 {framework} image.'
 
 

src/sagemaker/mxnet/model.py

@@ -15,7 +15,7 @@
 import logging
 
 import sagemaker
-from sagemaker.fw_utils import create_image_uri, model_code_key_prefix
+from sagemaker.fw_utils import create_image_uri, model_code_key_prefix, python_deprecation_warning
 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

src/sagemaker/sklearn/model.py

@@ -23,6 +23,7 @@
 
 logger = logging.getLogger('sagemaker')
 
+
 class SKLearnPredictor(RealTimePredictor):
     """A RealTimePredictor for inference against Scikit-learn Endpoints.
 

src/sagemaker/tensorflow/estimator.py

@@ -154,7 +154,7 @@ def run(self):
         """Run TensorBoard process."""
         port, tensorboard_process = self.create_tensorboard_process()
 
-        LOGGER.info('TensorBoard 0.1.7 at http://localhost:{}'.format(port))
+        logger.info('TensorBoard 0.1.7 at http://localhost:{}'.format(port))
         while not self.estimator.checkpoint_path:
             self.event.wait(1)
         with self._temporary_directory() as aws_sync_dir:
@@ -324,7 +324,7 @@ def fit_super():
             raise ValueError("Tensorboard is not supported with async fit")
 
         if self._script_mode_enabled() and run_tensorboard_locally:
-            LOGGER.warning(_SCRIPT_MODE_TENSORBOARD_WARNING.format(self.model_dir))
+            logger.warning(_SCRIPT_MODE_TENSORBOARD_WARNING.format(self.model_dir))
             fit_super()
         elif run_tensorboard_locally:
             tensorboard = Tensorboard(self)