Merge branch 'master' into pipeline-model-network-isolation

Author: ajaykarpur

src/sagemaker/model.py

@@ -791,7 +791,8 @@ def __init__(
                 authentication if they are provided; otherwise, python SDK will
                 try to use either CodeCommit credential helper or local
                 credential storage for authentication.
-            **kwargs: Keyword arguments passed to the ``Model`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/mxnet/model.py

@@ -107,8 +107,9 @@ def __init__(
             model_server_workers (int): Optional. The number of worker processes
                 used by the inference server. If None, server will use one
                 worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel``
-                initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/processing.py

@@ -21,6 +21,7 @@
 import pathlib
 
 from six.moves.urllib.parse import urlparse
+from six.moves.urllib.request import url2pathname
 
 from sagemaker import s3
 from sagemaker.job import _Job
@@ -535,21 +536,22 @@ def _handle_user_code_url(self, code):
             user_code_s3_uri = code
         elif code_url.scheme == "" or code_url.scheme == "file":
             # Validate that the file exists locally and is not a directory.
-            if not os.path.exists(code):
+            code_path = url2pathname(code_url.path)
+            if not os.path.exists(code_path):
                 raise ValueError(
                     """code {} wasn't found. Please make sure that the file exists.
                     """.format(
                         code
                     )
                 )
-            if not os.path.isfile(code):
+            if not os.path.isfile(code_path):
                 raise ValueError(
                     """code {} must be a file, not a directory. Please pass a path to a file.
                     """.format(
                         code
                     )
                 )
-            user_code_s3_uri = self._upload_code(code)
+            user_code_s3_uri = self._upload_code(code_path)
         else:
             raise ValueError(
                 "code {} url scheme {} is not recognized. Please pass a file path or S3 url".format(

src/sagemaker/pytorch/model.py

@@ -75,7 +75,7 @@ def __init__(
         model_server_workers=None,
         **kwargs
     ):
-        """Initialize an PyTorchModel.
+        """Initialize a PyTorchModel.
 
         Args:
             model_data (str): The S3 location of a SageMaker model data
@@ -106,8 +106,9 @@ def __init__(
             model_server_workers (int): Optional. The number of worker processes
                 used by the inference server. If None, server will use one
                 worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel``
-                initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/tensorflow/model.py

@@ -175,7 +175,9 @@ def __init__(
                 to call to create a predictor with an endpoint name and
                 SageMaker ``Session``. If specified, ``deploy()`` returns the
                 result of invoking this function on the created endpoint name.
-            **kwargs: Keyword arguments passed to the ``Model`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::
 

src/sagemaker/xgboost/model.py

@@ -90,7 +90,9 @@ def __init__(
                 created endpoint name.
             model_server_workers (int): Optional. The number of worker processes used by the
                 inference server. If None, server will use one worker per vCPU.
-            **kwargs: Keyword arguments passed to the ``FrameworkModel`` initializer.
+            **kwargs: Keyword arguments passed to the superclass
+                :class:`~sagemaker.model.FrameworkModel` and, subsequently, its
+                superclass :class:`~sagemaker.model.Model`.
 
         .. tip::