breaking: refactor Predictor attribute endpoint to endpoint_name (#1632)

Author: metrizable

doc/amazon_sagemaker_model_monitoring.rst

@@ -125,7 +125,7 @@ Using ``DefaultMonitor.create_monitoring_schedule()``, you can create a model mo
 
     my_monitor.create_monitoring_schedule(
         monitor_schedule_name='my-monitoring-schedule',
-        endpoint_input=predictor.endpoint,
+        endpoint_input=predictor.endpoint_name,
         statistics=my_monitor.baseline_statistics(),
         constraints=my_monitor.suggested_constraints(),
         schedule_cron_expression=CronExpressionGenerator.hourly(),

doc/frameworks/tensorflow/deploying_tensorflow_serving.rst

@@ -578,7 +578,7 @@ additional ``Predictor`` instances. Here's how:
   # ... continuing from the previous example
 
   # get the endpoint name from the default predictor
-  endpoint = predictor.endpoint
+  endpoint = predictor.endpoint_name
 
   # get a predictor for 'model2'
   model2_predictor = Predictor(endpoint, model_name='model2')

src/sagemaker/amazon/factorization_machines.py

@@ -278,14 +278,18 @@ class FactorizationMachinesPredictor(Predictor):
     https://docs.aws.amazon.com/sagemaker/latest/dg/fm-in-formats.html
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(FactorizationMachinesPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/ipinsights.py

@@ -184,14 +184,21 @@ class IPInsightsPredictor(Predictor):
     second column should contain the IPv4 address in dot notation.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(IPInsightsPredictor, self).__init__(
-            endpoint, sagemaker_session, serializer=csv_serializer, deserializer=json_deserializer
+            endpoint_name,
+            sagemaker_session,
+            serializer=csv_serializer,
+            deserializer=json_deserializer,
         )
 
 

src/sagemaker/amazon/kmeans.py

@@ -209,14 +209,18 @@ class KMeansPredictor(Predictor):
     ``closest_cluster`` key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(KMeansPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/knn.py

@@ -197,14 +197,18 @@ class KNNPredictor(Predictor):
     key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(KNNPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/lda.py

@@ -181,14 +181,18 @@ class LDAPredictor(Predictor):
     ``projection`` key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(LDAPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/linear_learner.py

@@ -442,14 +442,18 @@ class LinearLearnerPredictor(Predictor):
     key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(LinearLearnerPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/ntm.py

@@ -211,14 +211,18 @@ class NTMPredictor(Predictor):
     ``projection`` key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(NTMPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),

src/sagemaker/amazon/pca.py

@@ -193,14 +193,18 @@ class PCAPredictor(Predictor):
     ``projection`` key of the ``Record.label`` field.
     """
 
-    def __init__(self, endpoint, sagemaker_session=None):
+    def __init__(self, endpoint_name, sagemaker_session=None):
         """
         Args:
-            endpoint:
-            sagemaker_session:
+            endpoint_name (str): Name of the Amazon SageMaker endpoint to which
+                requests are sent.
+            sagemaker_session (sagemaker.session.Session): A SageMaker Session
+                object, used for SageMaker interactions (default: None). If not
+                specified, one is created using the default AWS configuration
+                chain.
         """
         super(PCAPredictor, self).__init__(
-            endpoint,
+            endpoint_name,
             sagemaker_session,
             serializer=numpy_to_record_serializer(),
             deserializer=record_deserializer(),