feature: Allow selecting inference response content for automl generated models #1566
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added 2 commits
June 10, 2020 11:59
1. Added attach() method to AutoML to allow attaching an AutoML object to an existing AutoMLJob 2. Added create_model() method to AutoML that returns a PipelineModel that can be used by the 3. Added a util function validate_and_update_inference_response() to update the inference container list based on the requested inference response keys 4. Updated and added unit tests
1. Added attach() method to AutoML to allow attaching an AutoML object to an existing AutoMLJob 2. Added create_model() method to AutoML that returns a PipelineModel that can be used by the 3. Added a util function validate_and_update_inference_response() to update the inference container list based on the requested inference response keys 4. Updated and added unit tests
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wiltonwu
reviewed
Jun 12, 2020
| @@ -187,49 +248,29 @@ def list_candidates( | |||
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| return self.sagemaker_session.list_candidates(**list_candidates_args)["Candidates"] | |||
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| def deploy( | |||
| def create_model( | |||
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Should this actually be private? I don't see a way to deploy an already created model here, maybe it exists outside of automl.py?
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no. I purposefully introduced the method create_model as public facing APIs. This does not really create the sagemaker model, but it allows to use the generated PipelineModel to perform batch transform as well.
see the test for an example usecase
wiltonwu
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Jun 12, 2020
nadiaya
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Jun 12, 2020
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…ted models (aws#1566) * Added attach() method to AutoML to allow attaching an AutoML object to an existing AutoMLJob * Added create_model() method to AutoML that returns a PipelineModel that can be used by the * Added a util function validate_and_update_inference_response() to update the inference container list based on the requested inference response keys * Updated and added unit tests
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* Feature: Support GPU training recipes with Sagemaker Python SDK (#1516) * v0 estimator for launching kandinksy training * code cleanup * option to over-ride git repos for kandinsky for testing purposes * update dependencies * update comment * formatting fixes * style fixes * code cleanup * Add warning messages for ingored arguments * cleanup, address comments * fix * clone launcher repo only if necessary * add a cleanup method to call after fit * fix docstring * fix warning * cleanup update * fix * code style fix * rename cleanup method for clarity * missed change * move cleanup to when object is destroyed * add unit tests * formatting fix * removing tests which don't work as recipe repos are private * removing tests which don't work as recipe repos are private * resolve comments * resolve comments * Feature: Support Neuron training recipes. (#1526) * Feature: Resolve recipes correctly before launching (#1529) * fix to work with launcher recipes * fix suffix for temp file * fix path and error message * fix for recipes from launcher * resolve recipes correctly * fix imports * reformat message to avoid code-doc test issue * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * doc formatting * check if resolver exists before registering * Feature: Add unit tests for recipes and minor bug fixes. (#1532) * basic checks and unit test for recipes * More testing for recipes. Move recipe overrides to top before accessing any recipe fields. * check that we use customer provided image uri if it is set * reformat * test fixes * update git urls for recipes * revert to ssh git urls for recipes * Feature: Move image uris and git repos for training recipes to json (#1547) * Update MANIFEST.in so that wheel builds correctly (#1563) * Remove default values for fields in recipe_overrides and fix recipe path. (#1566) * add optional source dir for recipes, copy training code and requirements to source dir * diff names for recipe file and local script option * format and add unit test * make entry point script and recipe file temp files that can be gced * formatting and fix * test fix * test fixes * format fix * break function up because it is too long * fixes * fix * fix * remove references to launcher and adapter dir as we copy out everything needed into source dir * reformat * copy all directory contents for trainium as there is more than one source file * fix * fix * remove debugging message * Change default source directory to current, add option to specify source dir (#1593) * update to public uris for hyperpod recipe repos and smp image * fixes * remove debug copies * change caps for env vars * skip some tests for now * format * neuron json for retrieving images * update training_recipes.json * add unit test * reformat * fix long line * add source dir check when using training recipe * adding more regions * reformat * doc update * doc update * doc update * doc update * fix capitalization issues * fix capitalization issues * doc check issue
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* Feature: Support GPU training recipes with Sagemaker Python SDK (#1516) * v0 estimator for launching kandinksy training * code cleanup * option to over-ride git repos for kandinsky for testing purposes * update dependencies * update comment * formatting fixes * style fixes * code cleanup * Add warning messages for ingored arguments * cleanup, address comments * fix * clone launcher repo only if necessary * add a cleanup method to call after fit * fix docstring * fix warning * cleanup update * fix * code style fix * rename cleanup method for clarity * missed change * move cleanup to when object is destroyed * add unit tests * formatting fix * removing tests which don't work as recipe repos are private * removing tests which don't work as recipe repos are private * resolve comments * resolve comments * Feature: Support Neuron training recipes. (#1526) * Feature: Resolve recipes correctly before launching (#1529) * fix to work with launcher recipes * fix suffix for temp file * fix path and error message * fix for recipes from launcher * resolve recipes correctly * fix imports * reformat message to avoid code-doc test issue * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * code style fix * doc formatting * check if resolver exists before registering * Feature: Add unit tests for recipes and minor bug fixes. (#1532) * basic checks and unit test for recipes * More testing for recipes. Move recipe overrides to top before accessing any recipe fields. * check that we use customer provided image uri if it is set * reformat * test fixes * update git urls for recipes * revert to ssh git urls for recipes * Feature: Move image uris and git repos for training recipes to json (#1547) * Update MANIFEST.in so that wheel builds correctly (#1563) * Remove default values for fields in recipe_overrides and fix recipe path. (#1566) * add optional source dir for recipes, copy training code and requirements to source dir * diff names for recipe file and local script option * format and add unit test * make entry point script and recipe file temp files that can be gced * formatting and fix * test fix * test fixes * format fix * break function up because it is too long * fixes * fix * fix * remove references to launcher and adapter dir as we copy out everything needed into source dir * reformat * copy all directory contents for trainium as there is more than one source file * fix * fix * remove debugging message * Change default source directory to current, add option to specify source dir (#1593) * update to public uris for hyperpod recipe repos and smp image * fixes * remove debug copies * change caps for env vars * skip some tests for now * format * neuron json for retrieving images * update training_recipes.json * add unit test * reformat * fix long line * add source dir check when using training recipe * adding more regions * reformat * doc update * doc update * doc update * doc update * fix capitalization issues * fix capitalization issues * doc check issue
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Description of changes:
Allow selecting inference response content for Autopilot generated models
Added attach() method to AutoML to allow attaching an AutoML object
to an existing SageMaker AutoMLJob
Added create_model() method to AutoML class that returns a PipelineModel
that can be used to deploy or transform.
Added a utility function
validate_and_update_inference_response()to AutoMLclass to update the inference container list based on the requested inference
response keys.
Updated and added unit tests and integ tests
Testing done:
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Tests
unique_name_from_baseto create resource names in integ tests (if appropriate)By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.