fix: Add pagination for ListInferenceComponent API responses, address non-blocking comments (#1376)

Author: bhaoz

src/sagemaker/amazon/factorization_machines.py

@@ -293,6 +293,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for FactorizationMachinesPredictor class.
 
@@ -307,12 +308,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(FactorizationMachinesPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/ipinsights.py

@@ -196,6 +196,7 @@ def __init__(
         sagemaker_session=None,
         serializer=CSVSerializer(),
         deserializer=JSONDeserializer(),
+        component_name=None,
     ):
         """Creates object to be used to get dot product of entity nad IP address.
 
@@ -210,12 +211,15 @@ def __init__(
                 serializes input data to text/csv.
             deserializer (callable): Optional. Default parses JSON responses
                 using ``json.load(...)``.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(IPInsightsPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/kmeans.py

@@ -222,6 +222,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for KMeansPredictor class.
 
@@ -236,12 +237,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(KMeansPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/knn.py

@@ -213,6 +213,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Function to initialize KNNPredictor.
 
@@ -227,12 +228,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(KNNPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/lda.py

@@ -197,6 +197,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Creates "LDAPredictor" object to be used for transforming input vectors.
 
@@ -211,12 +212,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(LDAPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/linear_learner.py

@@ -466,6 +466,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for LinearLearnerPredictor.
 
@@ -480,12 +481,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(LinearLearnerPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/ntm.py

@@ -230,6 +230,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for NTMPredictor class.
 
@@ -244,12 +245,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(NTMPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/pca.py

@@ -210,6 +210,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for PCAPredictor.
 
@@ -224,12 +225,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(PCAPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/randomcutforest.py

@@ -183,6 +183,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for RandomCutForestPredictor class.
 
@@ -197,12 +198,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(RandomCutForestPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )