add missing files and address warning

Author: laurenyu

doc/index.rst

@@ -15,10 +15,11 @@ The SageMaker Python SDK consists of a few primary interfaces:
 
     estimators
     tuner
+    model
+    pipeline
     predictors
     transformer
     session
-    model
     analytics
 
 MXNet

doc/ipinsights.rst

@@ -0,0 +1,22 @@
+IP Insights
+-----------
+
+The Amazon SageMaker IP Insights algorithm.
+
+.. autoclass:: sagemaker.IPInsights
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :inherited-members:
+    :exclude-members: image, num_entity_vectors, vector_dim, batch_metrics_publish_interval, epochs, learning_rate,
+                      num_ip_encoder_layers, random_negative_sampling_rate, shuffled_negative_sampling_rate, weight_decay
+
+.. autoclass:: sagemaker.IPInsightsModel
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. autoclass:: sagemaker.IPInsightsPredictor
+    :members:
+    :undoc-members:
+    :show-inheritance:

doc/knn.rst

@@ -0,0 +1,22 @@
+K-Nearest Neighbors
+-------------------
+
+The Amazon SageMaker K-Nearest Neighbors (k-NN) algorithm.
+
+.. autoclass:: sagemaker.KNN
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :inherited-members:
+    :exclude-members: image, k, sample_size, predictor_type, dimension_reduction_target, dimension_reduction_type,
+                      index_metric, index_type, faiss_index_ivf_nlists, faiss_index_pq_m
+
+.. autoclass:: sagemaker.KNNModel
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. autoclass:: sagemaker.KNNPredictor
+    :members:
+    :undoc-members:
+    :show-inheritance:

doc/ntm.rst

@@ -1,5 +1,5 @@
 NTM
---------------------
+---
 
 The Amazon SageMaker NTM algorithm.
 

doc/object2vec.rst

@@ -0,0 +1,21 @@
+Object2Vec
+----------
+
+The Amazon SageMaker Object2Vec algorithm.
+
+.. autoclass:: sagemaker.Object2Vec
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :inherited-members:
+    :exclude-members: image, enc_dim, mini_batch_size, epochs, early_stopping_patience, early_stopping_tolerance,
+                      dropout, weight_decay, bucket_width, num_classes, mlp_layers, mlp_dim, mlp_activation,
+                      output_layer, optimizer, learning_rate, enc0_network, enc1_network, enc0_cnn_filter_width,
+                      enc1_cnn_filter_width, enc0_max_seq_len, enc1_max_seq_len, enc0_token_embedding_dim,
+                      enc1_token_embedding_dim, enc0_vocab_size, enc1_vocab_size, enc0_layers, enc1_layers,
+                      enc0_freeze_pretrained_embedding, enc1_freeze_pretrained_embedding
+
+.. autoclass:: sagemaker.Object2VecModel
+    :members:
+    :undoc-members:
+    :show-inheritance:

doc/randomcutforest

@@ -0,0 +1,22 @@
+Random Cut Forest
+-----------------
+
+The Amazon SageMaker Random Cut Forest (RCF) algorithm.
+
+.. autoclass:: sagemaker.RandomCutForest
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :inherited-members:
+    :exclude-members: image, eval_metrics, num_trees, num_samples_per_tree, feature_dim
+
+
+.. autoclass:: sagemaker.RandomCutForestModel
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. autoclass:: sagemaker.RandomCutForestPredictor
+    :members:
+    :undoc-members:
+    :show-inheritance:

doc/sagemaker.workflow.airflow.rst

@@ -37,6 +37,6 @@ deploy_config
 .. autofunction:: sagemaker.workflow.airflow.deploy_config
 
 deploy_config_from_estimator
-----------------
+----------------------------
 
-.. autofunction:: sagemaker.workflow.airflow.deploy_config_from_estimator
+.. autofunction:: sagemaker.workflow.airflow.deploy_config_from_estimator