feature: Adding serial inference pipeline support to RegisterModel Step #2405

sreedes · 2021-05-24T11:19:59Z

Issue #, if available:
#2291, #2014, #2485

Description of changes:
This change enables multiple models to be packed together and registered as a single model package version, so that the models could be run as an inference pipeline.

Updated the inputs for RegisterModelStep to also take a model object or a PipelineModel for Serial Inference pipeline
Performs repack in a loop for containers in a serial inference pipeline, if required.
Ability to invoke RegisterModelStep without an Estimator.
The environment variables are auto-updated by the framework classes into the model package

Testing done:
test_register_model_sip - Able to add more than 1 model during registration of model package.

Merge Checklist

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General

I have read the CONTRIBUTING doc
I used the commit message format described in CONTRIBUTING
I have passed the region in to all S3 and STS clients that I've initialized as part of this change.
I have updated any necessary documentation, including READMEs and API docs (if appropriate)

Tests

I have added tests that prove my fix is effective or that my feature works (if appropriate)
I have checked that my tests are not configured for a specific region or account (if appropriate)
I have used unique_name_from_base to 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.

sagemaker-bot · 2021-05-24T11:22:57Z

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danabens · 2021-06-06T22:49:36Z

src/sagemaker/workflow/_utils.py

        content_types,
        response_types,
        inference_instances,
        transform_instances,
+        model_data=None,


is this change necessary?

Yes, now that we are passing model list, this input may be empty, hence marked it as None.

danabens · 2021-06-06T22:51:00Z

src/sagemaker/workflow/_utils.py

@@ -225,6 +226,7 @@ def __init__(
        compile_model_family=None,
        description=None,
        depends_on: List[str] = None,
+        container_def_list=None,
        **kwargs,
    ):
        """Constructor of a register model step.


nit - see below that model_data is missing a type in the argument description. i.e. model_data: the S3... please add model_data (str): the S3...

sure i shall update.

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ahsan-z-khan · 2021-07-13T17:58:10Z

src/sagemaker/workflow/_utils.py

 from typing import List

+import sagemaker


why are we importing sagemaker here?

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src/sagemaker/model.py

feature: Adding serial inference pipeline support to RegisterModel Step

0a0ce3c

sreedes marked this pull request as draft May 24, 2021 11:23

Merge branch 'master' into model-registry-sip

5e90186

sreedes added 2 commits May 26, 2021 11:28

feature: Adding serial inference pipeline support to RegisterModel Step

6561856

feature: Adding serial inference pipeline support to RegisterModel Step

a4a352a

sreedes added 2 commits May 27, 2021 09:14

feature: Adding serial inference pipeline support to RegisterModel Step

f23ff20

feature: Adding serial inference pipeline support to RegisterModel Step

f52ab31

sreedes marked this pull request as ready for review June 2, 2021 18:10

danabens reviewed Jun 6, 2021

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Updating the input to model or pipeline model

c2d5e61

ahsan-z-khan reviewed Jul 13, 2021

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src/sagemaker/workflow/_utils.py Outdated

from typing import List

import sagemaker

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why are we importing sagemaker here?

sreedes requested a review from ahsan-z-khan July 14, 2021 05:57

Review comment incorporation

4a8672e

Fixing unit test failure

33db77f

Fixing unit test failure

a752214

ahsan-z-khan approved these changes Jul 14, 2021

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ahsan-z-khan merged commit 8f5b374 into aws:master Jul 14, 2021

akrishna1995 mentioned this pull request Dec 28, 2023

Environment Variable Not Passed into Docker Image When Registering Model #2291

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feature: Adding serial inference pipeline support to RegisterModel Step #2405

feature: Adding serial inference pipeline support to RegisterModel Step #2405

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