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Adding support for DataProcessing to SageMaker TransformJob #52

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Adding support for DataProcessing to SageMaker TransformJob #52

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14 changes: 10 additions & 4 deletions src/stepfunctions/steps/sagemaker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,7 @@ class TransformStep(Task):
Creates a Task State to execute a `SageMaker Transform Job <https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTransformJob.html>`_.
"""

def __init__(self, state_id, transformer, job_name, model_name, data, data_type='S3Prefix', content_type=None, compression_type=None, split_type=None, experiment_config=None, wait_for_completion=True, tags=None, **kwargs):
def __init__(self, state_id, transformer, job_name, model_name, data, data_type='S3Prefix', content_type=None, compression_type=None, split_type=None, experiment_config=None, wait_for_completion=True, tags=None, input_filter=None, output_filter=None, join_source=None, **kwargs):
"""
Args:
state_id (str): State name whose length **must be** less than or equal to 128 unicode characters. State names **must be** unique within the scope of the whole state machine.
Expand Down Expand Up @@ -150,7 +150,10 @@ def __init__(self, state_id, transformer, job_name, model_name, data, data_type=
content_type=content_type,
compression_type=compression_type,
split_type=split_type,
job_name=job_name
job_name=job_name,
input_filter=input_filter,
join_source=join_source,
output_filter=output_filter
)
else:
parameters = transform_config(
Expand All @@ -159,7 +162,10 @@ def __init__(self, state_id, transformer, job_name, model_name, data, data_type=
data_type=data_type,
content_type=content_type,
compression_type=compression_type,
split_type=split_type
split_type=split_type,
input_filter=input_filter,
join_source=join_source,
output_filter=output_filter
)

if isinstance(job_name, (ExecutionInput, StepInput)):
Expand Down Expand Up @@ -253,7 +259,7 @@ def __init__(self, state_id, endpoint_config_name, model_name, initial_instance_

if isinstance(data_capture_config, DataCaptureConfig):
parameters['DataCaptureConfig'] = data_capture_config._to_request_dict()

if tags:
parameters['Tags'] = tags_dict_to_kv_list(tags)

Expand Down
51 changes: 51 additions & 0 deletions tests/unit/test_sagemaker_steps.py
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Expand Up @@ -422,6 +422,57 @@ def test_transform_step_creation(pca_transformer):
'End': True
}

step_with_optional_fields = TransformStep('Inference',
transformer=pca_transformer,
data='s3://sagemaker/inference',
job_name='transform-job',
model_name='pca-model',
experiment_config={
'ExperimentName': 'pca_experiment',
'TrialName': 'pca_trial',
'TrialComponentDisplayName': 'Transform'
},
tags=DEFAULT_TAGS,
join_source='Input',
output_filter='$[2:]',
input_filter='$[1:]'
)
assert step_with_optional_fields.to_dict() == {
'Type': 'Task',
'Parameters': {
'ModelName': 'pca-model',
'TransformInput': {
'DataSource': {
'S3DataSource': {
'S3DataType': 'S3Prefix',
'S3Uri': 's3://sagemaker/inference'
}
}
},
'TransformOutput': {
'S3OutputPath': 's3://sagemaker/transform-output'
},
'TransformJobName': 'transform-job',
'TransformResources': {
'InstanceCount': 1,
'InstanceType': 'ml.c4.xlarge'
},
'DataProcessing': {
'InputFilter': '$[1:]',
'OutputFilter': '$[2:]',
'JoinSource': 'Input',
},
'ExperimentConfig': {
'ExperimentName': 'pca_experiment',
'TrialName': 'pca_trial',
'TrialComponentDisplayName': 'Transform'
},
'Tags': DEFAULT_TAGS_LIST
},
'Resource': 'arn:aws:states:::sagemaker:createTransformJob.sync',
'End': True
}

@patch('botocore.client.BaseClient._make_api_call', new=mock_boto_api_call)
def test_get_expected_model(pca_estimator):
training_step = TrainingStep('Training', estimator=pca_estimator, job_name='TrainingJob')
Expand Down