Merge branch 'aws:master' into master

Author: Snoyark

.githooks/pre-push

@@ -12,5 +12,5 @@ start_time=`date +%s`
 tox -e sphinx,doc8 --parallel all
 ./ci-scripts/displaytime.sh 'sphinx,doc8' $start_time
 start_time=`date +%s`
-tox -e py36,py37,py38,py39 --parallel all -- tests/unit
-./ci-scripts/displaytime.sh 'py36,py37,py38,py39 unit' $start_time
+tox -e py37,py38,py39 --parallel all -- tests/unit
+./ci-scripts/displaytime.sh 'py37,py38,py39 unit' $start_time

CHANGELOG.md

@@ -1,5 +1,80 @@
 # Changelog
 
+## v2.99.0 (2022-07-08)
+
+### Features
+
+ * heterogeneous cluster set up in distribution config
+ * support heterogeneous cluster for training
+ * include fields to work with inference recommender
+
+### Bug Fixes and Other Changes
+
+ * Moving the newly added field instance_group to the end of method
+ * image_uri does not need to be specified with instance_groups
+ * Loosen version of attrs dependency
+ * Add PipelineVariable annotation in estimatory, processing, tuner, transformer base classes
+ * model table link
+
+### Documentation Changes
+
+ * documentation for heterogeneous cluster
+
+## v2.98.0 (2022-07-05)
+
+### Features
+
+ * Adding deepar image
+
+### Documentation Changes
+
+ * edit to clarify how to use inference.py
+
+## v2.97.0 (2022-06-28)
+
+### Deprecations and Removals
+
+ * remove support for python 3.6
+
+### Features
+
+ * update prebuilt models documentation
+
+### Bug Fixes and Other Changes
+
+ * Skipping test_candidate_estimator_default_rerun_and_deploy
+ * Update model name from 'compiled.pt' to 'model.pth' for neo
+ * update pytest, skip hf integ temp
+ * Add override_pipeline_parameter_var decorator to give grace period to update invalid pipeline var args
+
+## v2.96.0 (2022-06-20)
+
+### Features
+
+ * Add helper method to generate pipeline adjacency list
+
+### Bug Fixes and Other Changes
+
+ * changing trcomp integ tests to be able to run in all regions
+
+## v2.95.0 (2022-06-16)
+
+### Features
+
+ * Adding Training Compiler support for TensorFlow estimator starting TF 2.9
+ * Add support for TF 2.9 training
+
+### Bug Fixes and Other Changes
+
+ * integs fallback from p3 to p2 instance
+ * bucket exists check for session.default_bucket
+ * make instance type fields as optional
+
+### Documentation Changes
+
+ * improvements on the docstring of ModelStep
+ * Add XGBoostProcessor
+
 ## v2.94.0 (2022-06-07)
 
 ### Features

README.rst

@@ -87,7 +87,6 @@ Supported Python Versions
 
 SageMaker Python SDK is tested on:
 
-- Python 3.6
 - Python 3.7
 - Python 3.8
 - Python 3.9

VERSION

@@ -1 +1 @@
-2.94.1.dev0
+2.99.1.dev0

doc/api/utility/instance_group.rst

@@ -0,0 +1,8 @@
+Instance Group
+--------------
+
+.. automodule:: sagemaker.instance_group
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :private-members:

doc/doc_utils/jumpstart_doc_utils.py

@@ -143,20 +143,26 @@ def create_jumpstart_model_table():
     file_content.append(".. |external-link| raw:: html\n\n")
     file_content.append('   <i class="fa fa-external-link"></i>\n\n')
 
-    file_content.append("==================================\n")
-    file_content.append("JumpStart Available Model Table\n")
-    file_content.append("==================================\n")
+    file_content.append("================================================\n")
+    file_content.append("Built-in Algorithms with pre-trained Model Table\n")
+    file_content.append("================================================\n")
     file_content.append(
         """
-    JumpStart for the SageMaker Python SDK uses model IDs and model versions to access the necessary
-    utilities. This table serves to provide the core material plus some extra information that can be useful
-    in selecting the correct model ID and corresponding parameters.\n"""
+    The SageMaker Python SDK uses model IDs and model versions to access the necessary
+    utilities for pre-trained models. This table serves to provide the core material plus
+    some extra information that can be useful in selecting the correct model ID and
+    corresponding parameters.\n"""
     )
     file_content.append(
         """
     If you want to automatically use the latest version of the model, use "*" for the `model_version` attribute.
     We highly suggest pinning an exact model version however.\n"""
     )
+    file_content.append(
+        """
+    These models are also available through the
+    `JumpStart UI in SageMaker Studio <https://docs.aws.amazon.com/sagemaker/latest/dg/studio-jumpstart.html>`__\n"""
+    )
     file_content.append("\n")
     file_content.append(".. list-table:: Available Models\n")
     file_content.append("   :widths: 50 20 20 20 30 20\n")
@@ -183,5 +189,6 @@ def create_jumpstart_model_table():
             "     - `{} <{}>`__ |external-link|\n".format(model_source, model_spec["url"])
         )
 
-    f = open("doc_utils/jumpstart.rst", "w")
+    f = open("doc_utils/pretrainedmodels.rst", "w")
     f.writelines(file_content)
+    f.close()

doc/doc_utils/jumpstart.rst renamed to doc/doc_utils/pretrainedmodels.rst

@@ -10,6 +10,14 @@ TensorFlow Estimator
     :undoc-members:
     :show-inheritance:
 
+TensorFlow Training Compiler Configuration
+------------------------------------------
+
+.. autoclass:: sagemaker.tensorflow.TrainingCompilerConfig
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 TensorFlow Serving Model
 ------------------------
 

doc/frameworks/tensorflow/sagemaker.tensorflow.rst

@@ -759,7 +759,7 @@ Create Python Scripts for Custom Input and Output Formats
 ---------------------------------------------------------
 
 You can add your customized Python code to process your input and output data.
-This customized Python code must be named ``inference.py`` and specified through the ``entry_point`` parameter:
+This customized Python code must be named ``inference.py`` and is specified through the ``entry_point`` parameter:
 
 .. code::
 
@@ -769,6 +769,8 @@ This customized Python code must be named ``inference.py`` and specified through
                             model_data='s3://mybucket/model.tar.gz',
                             role='MySageMakerRole')
 
+In the example above, ``inference.py`` is assumed to be a file inside ``model.tar.gz``. If you want to use a local file instead, you must add the ``source_dir`` argument. See the documentation on `TensorFlowModel <https://sagemaker.readthedocs.io/en/stable/frameworks/tensorflow/sagemaker.tensorflow.html#sagemaker.tensorflow.model.TensorFlowModel>`_.
+
 How to implement the pre- and/or post-processing handler(s)
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^