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feat: Add additional PipelineVariable support to ModelTrainer #5533

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feat: Add additional PipelineVariable support to ModelTrainer #5533

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c9437cb
Update integration test
admivsn Feb 2, 2026
9ed75a9
Add missing pipeline parameters
admivsn Feb 2, 2026
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41 changes: 24 additions & 17 deletions sagemaker-mlops/tests/integ/test_pipeline_train_registry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,27 @@ def test_pipeline_with_train_and_registry(sagemaker_session, pipeline_session, r

# Parameters
processing_instance_count = ParameterInteger(name="ProcessingInstanceCount", default_value=1)
processing_image_uri = ParameterString(
name="ProcessingImageUri",
default_value=image_uris.retrieve(
framework="sklearn",
region=region,
version="1.2-1",
py_version="py3",
instance_type="ml.m5.xlarge",
),
)
training_instance_count = ParameterInteger(name="TrainingInstanceCount", default_value=1)
training_image_uri = ParameterString(
name="TrainingImageUri",
default_value=image_uris.retrieve(
framework="xgboost",
region=region,
version="1.0-1",
py_version="py3",
instance_type="ml.m5.xlarge",
),
)
instance_type = ParameterString(name="InstanceType", default_value="ml.m5.xlarge")
input_data = ParameterString(
name="InputDataUrl",
Expand All @@ -65,13 +85,7 @@ def test_pipeline_with_train_and_registry(sagemaker_session, pipeline_session, r

# Processing step
sklearn_processor = ScriptProcessor(
image_uri=image_uris.retrieve(
framework="sklearn",
region=region,
version="1.2-1",
py_version="py3",
instance_type="ml.m5.xlarge",
),
image_uri=processing_image_uri,
instance_type=instance_type,
instance_count=processing_instance_count,
base_job_name=f"{base_job_prefix}-sklearn",
Expand Down Expand Up @@ -128,17 +142,8 @@ def test_pipeline_with_train_and_registry(sagemaker_session, pipeline_session, r
cache_config=cache_config,
)

# Training step
image_uri = image_uris.retrieve(
framework="xgboost",
region=region,
version="1.0-1",
py_version="py3",
instance_type="ml.m5.xlarge",
)

model_trainer = ModelTrainer(
training_image=image_uri,
training_image=training_image_uri,
compute=Compute(instance_type=instance_type, instance_count=training_instance_count),
base_job_name=f"{base_job_prefix}-xgboost",
sagemaker_session=pipeline_session,
Expand Down Expand Up @@ -195,7 +200,9 @@ def test_pipeline_with_train_and_registry(sagemaker_session, pipeline_session, r
name=pipeline_name,
parameters=[
processing_instance_count,
processing_image_uri,
training_instance_count,
training_image_uri,
instance_type,
input_data,
hyper_parameter_objective,
Expand Down