doc: add link to Amazon algorithm estimator parent class to clarify **kwargs

src/sagemaker/amazon/amazon_estimator.py

@@ -49,15 +49,27 @@ def __init__(
         """Initialize an AmazonAlgorithmEstimatorBase.
 
         Args:
-            role:
-            train_instance_count:
-            train_instance_type:
+            role (str): An AWS IAM role (either name or full ARN). The Amazon
+                SageMaker training jobs and APIs that create Amazon SageMaker
+                endpoints use this role to access training data and model
+                artifacts. After the endpoint is created, the inference code
+                might use the IAM role, if it needs to access an AWS resource.
+            train_instance_count (int): Number of Amazon EC2 instances to use
+                for training.
+            train_instance_type (str): Type of EC2 instance to use for training,
+                for example, 'ml.c4.xlarge'.
             data_location (str or None): The s3 prefix to upload RecordSet
                 objects to, expressed as an S3 url. For example
                 "s3://example-bucket/some-key-prefix/". Objects will be saved in
                 a unique sub-directory of the specified location. If None, a
                 default data location will be used.
-            **kwargs:
+            **kwargs: Additional parameters passed to
+                :class:`~sagemaker.estimator.EstimatorBase`.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
 
         if "enable_network_isolation" in kwargs:

src/sagemaker/amazon/factorization_machines.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -205,6 +205,12 @@ def __init__(
                 that takes effect when factors_init_method parameter is
                 'constant'.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         super(FactorizationMachines, self).__init__(
             role, train_instance_count, train_instance_type, **kwargs

src/sagemaker/amazon/ipinsights.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -119,6 +119,12 @@ def __init__(
             weight_decay (float): Optional. Weight decay coefficient. Adds L2
                 regularization.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         super(IPInsights, self).__init__(role, train_instance_count, train_instance_type, **kwargs)
         self.num_entity_vectors = num_entity_vectors

src/sagemaker/amazon/kmeans.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -135,6 +135,12 @@ def __init__(
                 is provided, the score shall be reported in terms of all
                 requested metrics.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         super(KMeans, self).__init__(role, train_instance_count, train_instance_type, **kwargs)
         self.k = k

src/sagemaker/amazon/knn.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -128,6 +128,12 @@ def __init__(
             faiss_index_pq_m (int): Optional. Number of vector sub-components to
                 construct in the index, if index_type is "faiss.IVFPQ".
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
 
         super(KNN, self).__init__(role, train_instance_count, train_instance_type, **kwargs)

src/sagemaker/amazon/lda.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -106,6 +106,12 @@ def __init__(
             tol (float): Optional. Target error tolerance for the ALS phase of
                 the algorithm.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         # this algorithm only supports single instance training
         if kwargs.pop("train_instance_count", 1) != 1:

src/sagemaker/amazon/linear_learner.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -318,6 +318,12 @@ def __init__(
                 which give each class equal importance in the loss function. Only used when
                 predictor_type is multiclass_classifier.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         super(LinearLearner, self).__init__(
             role, train_instance_count, train_instance_type, **kwargs

src/sagemaker/amazon/ntm.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -139,6 +139,12 @@ def __init__(
                 regularization.
             learning_rate (float): Optional. Learning rate for the optimizer.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
 
         super(NTM, self).__init__(role, train_instance_count, train_instance_type, **kwargs)

src/sagemaker/amazon/object2vec.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -255,6 +255,12 @@ def __init__(
             enc1_freeze_pretrained_embedding (bool): Optional. Freeze pretrained
                 embedding weights
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
 
         super(Object2Vec, self).__init__(role, train_instance_count, train_instance_type, **kwargs)

src/sagemaker/amazon/pca.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -113,6 +113,12 @@ def __init__(
                 default value equal to the maximum of 10 and num_components will
                 be used. Valid for randomized mode only.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
         super(PCA, self).__init__(role, train_instance_count, train_instance_type, **kwargs)
         self.num_components = num_components

src/sagemaker/amazon/randomcutforest.py

@@ -1,4 +1,4 @@
-# Copyright 2017-2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -104,6 +104,12 @@ def __init__(
                 precision, recall, and f1 scores. If test data is provided, the
                 score shall be reported in terms of all requested metrics.
             **kwargs: base class keyword argument values.
+
+        .. tip::
+
+            You can find additional parameters for initializing this class at
+            :class:`~sagemaker.estimator.amazon_estimator.AmazonAlgorithmEstimatorBase` and
+            :class:`~sagemaker.estimator.EstimatorBase`.
         """
 
         super(RandomCutForest, self).__init__(