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‎CHANGELOG.md

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# Changelog
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## v2.52.2 (2021-08-10)
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### Bug Fixes and Other Changes
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* sklearn integ tests, remove swallowing exception on feature group delete attempt
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* sklearn integ test for custom bucket
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### Documentation Changes
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* Fix dataset_definition links
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* Document LambdaModel and LambdaPredictor classes
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## v2.52.1 (2021-08-06)
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### Bug Fixes and Other Changes
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* revert #2251 changes for sklearn processor
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## v2.52.0 (2021-08-05)
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### Features
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* processors that support multiple Python files, requirements.txt, and dependencies.
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* support step object in step depends on list
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### Bug Fixes and Other Changes
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* enable isolation while creating model from job
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* update `sagemaker.serverless` integration test
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* Use correct boto model name for RegisterModelStep properties
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## v2.51.0 (2021-08-03)
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### Features
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* add LambdaStep support for SageMaker Pipelines
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* support JsonGet for all step types
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## v2.50.1 (2021-08-02)
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### Bug Fixes and Other Changes
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* null checks for uploaded_code and entry_point
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### Documentation Changes
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* update sagemaker.estimator.EstimatorBase
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* Mark baseline as optional in KernelSHAP.
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## v2.50.0 (2021-07-28)
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### Features
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* add KIX region to image_uris
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### Bug Fixes and Other Changes
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* Rename `PredictorBase.delete_endpoint` as `PredictorBase.delete_predictor`
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* incorrect default argument for callback output parameter
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### Documentation Changes
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* Remove years from copyright boilerplate
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* Fix documentation formatting for PySpark and SparkJar processors
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### Testing and Release Infrastructure
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* enable py38 tox env
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## v2.49.2 (2021-07-21)
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### Bug Fixes and Other Changes
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* order of populating container list
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* upgrade Adobe Analytics cookie to 3.0
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## v2.49.1 (2021-07-19)
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### Bug Fixes and Other Changes

‎NOTICE.txt

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Amazon SageMaker Python SDK
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Copyright 2017-2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

‎README.rst

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Licensing
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~~~~~~~~~
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SageMaker Python SDK is licensed under the Apache 2.0 License. It is copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. The license is available at:
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SageMaker Python SDK is licensed under the Apache 2.0 License. It is copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. The license is available at:
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http://aws.amazon.com/apache2.0/
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Running tests

‎VERSION

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2.49.2.dev0
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2.52.3.dev0

‎ci-scripts/displaytime.sh

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#!/usr/bin/env bash
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# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"). You
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# may not use this file except in compliance with the License. A copy of

‎ci-scripts/queue_build.py

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# Copyright 2019-2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"). You
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# may not use this file except in compliance with the License. A copy of

‎doc/_static/aws-ux-shortbread/index.js

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‎doc/_static/aws-ux-shortbread/init.js

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(function (w) {
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w.URLSearchParams = w.URLSearchParams || function (searchString) {
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var self = this;
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self.searchString = searchString;
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self.get = function (name) {
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var results = new RegExp('[\?&]' + name + '=([^&#]*)').exec(self.searchString);
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if (results === null) {
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return null;
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}
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else {
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return decodeURI(results[1]) || 0;
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}
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};
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}
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})(window);
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const queryString = window.location.search;
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const urlParams = new URLSearchParams(queryString);
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const lang = urlParams.get('lang')
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window.onload = function () {
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var domainName = window.location.hostname;
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// remove an instance of shortbread if already exists
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var existingShortbreadEl = document.getElementById("awsccc-sb-ux-c");
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existingShortbreadEl && existingShortbreadEl.remove();
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var shortbread = AWSCShortbread({
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domain: domainName,
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language: lang,
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//queryGeolocation: function (geolocatedIn) { geolocatedIn("EU") },
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});
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shortbread.checkForCookieConsent();
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}

‎doc/api/inference/model.rst

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:members:
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:undoc-members:
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:show-inheritance:
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.. autoclass:: sagemaker.serverless.model.LambdaModel
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/inference/predictors.rst

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:members:
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:show-inheritance:
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.. autoclass:: sagemaker.serverless.predictor.LambdaPredictor
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/utility/lambda_helper.rst

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Lambda Utilities
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----------------
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.. automodule:: sagemaker.lambda_helper
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/conf.py

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# Copyright 2017-2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"). You
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htmlhelp_basename = "%sdoc" % project
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html_js_files = ["https://a0.awsstatic.com/s_code/js/1.0/awshome_s_code.js", "js/analytics.js"]
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# For Adobe Analytics
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html_js_files = [
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"https://a0.awsstatic.com/s_code/js/3.0/awshome_s_code.js",
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"aws-ux-shortbread/index.js",
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"aws-ux-shortbread/init.js",
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]
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‎doc/overview.rst

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For information about using sample notebooks in a SageMaker notebook instance, see `Use Example Notebooks <https://docs.aws.amazon.com/sagemaker/latest/dg/howitworks-nbexamples.html>`__
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********************
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Serverless Inference
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********************
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You can use the SageMaker Python SDK to perform serverless inference on Lambda.
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To deploy models to Lambda, you must complete the following prerequisites:
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- `Package your model and inference code as a container image. <https://docs.aws.amazon.com/lambda/latest/dg/images-create.html>`_
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- `Create a role that lists Lambda as a trusted entity. <https://docs.aws.amazon.com/lambda/latest/dg/lambda-intro-execution-role.html#permissions-executionrole-console>`_
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After completing the prerequisites, you can deploy your model to Lambda using
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.. code:: python
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from sagemaker.serverless import LambdaModel
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role = "arn:aws:iam::123456789012:role/MyLambdaExecutionRole"
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model = LambdaModel(image_uri=image_uri, role=role)
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predictor = model.deploy("my-lambda-function", timeout=20, memory_size=4092)
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.. code:: python
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methods.
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.. _LambdaModel : https://sagemaker.readthedocs.io/en/stable/api/inference/model.html#sagemaker.serverless.model.LambdaModel
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.. _LambdaPredictor : https://sagemaker.readthedocs.io/en/stable/api/inference/predictors.html#sagemaker.serverless.predictor.LambdaPredictor
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******************
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SageMaker Workflow
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******************

‎doc/workflows/pipelines/index.rst

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Amazon Pipelines
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###################
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SageMaker Pipelines
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###################
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SageMaker APIs for creating and managing Amazon Pipelines.
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SageMaker APIs for creating and managing SageMaker Pipelines.
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‎doc/workflows/pipelines/sagemaker.workflow.pipelines.rst

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‎setup.py

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‎src/sagemaker/__init__.py

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‎src/sagemaker/_studio.py

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‎src/sagemaker/algorithm.py

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‎src/sagemaker/amazon/__init__.py

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‎src/sagemaker/amazon/amazon_estimator.py

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‎src/sagemaker/amazon/common.py

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‎src/sagemaker/amazon/factorization_machines.py

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‎src/sagemaker/amazon/hyperparameter.py

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‎src/sagemaker/amazon/ipinsights.py

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‎src/sagemaker/amazon/kmeans.py

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‎src/sagemaker/amazon/knn.py

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