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fix: make 'ModelInput' field optional for inference recommendation #3220

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Merged
merged 4 commits into from
Jul 12, 2022
Merged

fix: make 'ModelInput' field optional for inference recommendation #3220

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1f3fbe7
fix: make 'ModelInput' field optional for inference recommendation
rahven14 Jul 8, 2022
037a574
Merge branch 'aws:master' into fix/update-inference-recommender-fields
rahven14 Jul 11, 2022
f536d35
fix: refactor code to conditionally update container object
rahven14 Jul 11, 2022
e51e492
Merge branch 'fix/update-inference-recommender-fields' of https://git…
rahven14 Jul 11, 2022
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71 changes: 47 additions & 24 deletions src/sagemaker/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -749,32 +749,55 @@ def update_container_with_inference_params(
dict: dict with inference recommender params
"""

if (
framework is not None
and framework_version is not None
and nearest_model_name is not None
and data_input_configuration is not None
):
if framework is not None and framework_version is not None and nearest_model_name is not None:
if container_list is not None:
for obj in container_list:
obj.update(
{
"Framework": framework,
"FrameworkVersion": framework_version,
"NearestModelName": nearest_model_name,
"ModelInput": {
"DataInputConfig": data_input_configuration,
},
}
construct_container_object(
obj, data_input_configuration, framework, framework_version, nearest_model_name
)
if container_obj is not None:
container_obj.update(
{
"Framework": framework,
"FrameworkVersion": framework_version,
"NearestModelName": nearest_model_name,
"ModelInput": {
"DataInputConfig": data_input_configuration,
},
}
construct_container_object(
container_obj,
data_input_configuration,
framework,
framework_version,
nearest_model_name,
)


def construct_container_object(
obj, data_input_configuration, framework, framework_version, nearest_model_name
):
"""Function to construct container object.

Args:
framework (str): Machine learning framework of the model package container image
(default: None).
framework_version (str): Framework version of the Model Package Container Image
(default: None).
nearest_model_name (str): Name of a pre-trained machine learning benchmarked by
Amazon SageMaker Inference Recommender (default: None).
data_input_configuration (str): Input object for the model (default: None).
container_obj (dict): object to be updated.
container_list (list): list to be updated.

Returns:
dict: container object
"""

obj.update(
{
"Framework": framework,
"FrameworkVersion": framework_version,
"NearestModelName": nearest_model_name,
}
)

if data_input_configuration is not None:
obj.update(
{
"ModelInput": {
"DataInputConfig": data_input_configuration,
},
}
)
6 changes: 0 additions & 6 deletions tests/integ/sagemaker/workflow/test_model_create_and_registration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,6 @@ def test_conditional_pytorch_training_model_registration(
framework = "TENSORFLOW"
framework_version = "2.9"
nearest_model_name = "resnet50"
data_input_configuration = '{"input_1":[1,224,224,3]}'

# If image_uri is not provided, the instance_type should not be a pipeline variable
# since instance_type is used to retrieve image_uri in compile time (PySDK)
Expand Down Expand Up @@ -132,7 +131,6 @@ def test_conditional_pytorch_training_model_registration(
framework=framework,
framework_version=framework_version,
nearest_model_name=nearest_model_name,
data_input_configuration=data_input_configuration,
)

model = Model(
Expand Down Expand Up @@ -219,7 +217,6 @@ def test_mxnet_model_registration(
framework = "TENSORFLOW"
framework_version = "2.9"
nearest_model_name = "resnet50"
data_input_configuration = '{"input_1":[1,224,224,3]}'

model = MXNetModel(
entry_point=entry_point,
Expand All @@ -244,7 +241,6 @@ def test_mxnet_model_registration(
framework=framework,
framework_version=framework_version,
nearest_model_name=nearest_model_name,
data_input_configuration=data_input_configuration,
)

pipeline = Pipeline(
Expand Down Expand Up @@ -293,7 +289,6 @@ def test_sklearn_xgboost_sip_model_registration(
framework = "TENSORFLOW"
framework_version = "2.9"
nearest_model_name = "resnet50"
data_input_configuration = '{"input_1":[1,224,224,3]}'

# The instance_type should not be a pipeline variable
# since it is used to retrieve image_uri in compile time (PySDK)
Expand Down Expand Up @@ -450,7 +445,6 @@ def test_sklearn_xgboost_sip_model_registration(
framework=framework,
framework_version=framework_version,
nearest_model_name=nearest_model_name,
data_input_configuration=data_input_configuration,
)

pipeline = Pipeline(
Expand Down
4 changes: 0 additions & 4 deletions tests/unit/sagemaker/workflow/test_pipeline_session.py
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Original file line number Diff line number Diff line change
Expand Up @@ -151,7 +151,6 @@ def test_pipeline_session_context_for_model_step_without_instance_types(
framework="TENSORFLOW",
framework_version="2.9",
nearest_model_name="resnet50",
data_input_configuration='{"input_1":[1,224,224,3]}',
)

expected_output = {
Expand All @@ -173,9 +172,6 @@ def test_pipeline_session_context_for_model_step_without_instance_types(
"Framework": "TENSORFLOW",
"FrameworkVersion": "2.9",
"NearestModelName": "resnet50",
"ModelInput": {
"DataInputConfig": '{"input_1":[1,224,224,3]}',
},
}
],
"SupportedContentTypes": ["text/csv"],
Expand Down
9 changes: 0 additions & 9 deletions tests/unit/sagemaker/workflow/test_step_collections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -446,7 +446,6 @@ def test_register_model_tf(estimator_tf, model_metrics, drift_check_baselines):
framework="TENSORFLOW",
framework_version="2.9",
nearest_model_name="resnet50",
data_input_configuration='{"input_1":[1,224,224,3]}',
)
assert ordered(register_model.request_dicts()) == ordered(
[
Expand Down Expand Up @@ -523,7 +522,6 @@ def test_register_model_sip(estimator, model_metrics, drift_check_baselines):
framework="TENSORFLOW",
framework_version="2.9",
nearest_model_name="resnet50",
data_input_configuration='{"input_1":[1,224,224,3]}',
)
assert ordered(register_model.request_dicts()) == ordered(
[
Expand All @@ -542,9 +540,6 @@ def test_register_model_sip(estimator, model_metrics, drift_check_baselines):
"Framework": "TENSORFLOW",
"FrameworkVersion": "2.9",
"NearestModelName": "resnet50",
"ModelInput": {
"DataInputConfig": '{"input_1":[1,224,224,3]}',
},
},
{
"Image": "fakeimage2",
Expand All @@ -553,9 +548,6 @@ def test_register_model_sip(estimator, model_metrics, drift_check_baselines):
"Framework": "TENSORFLOW",
"FrameworkVersion": "2.9",
"NearestModelName": "resnet50",
"ModelInput": {
"DataInputConfig": '{"input_1":[1,224,224,3]}',
},
},
],
"SupportedContentTypes": ["content_type"],
Expand Down Expand Up @@ -619,7 +611,6 @@ def test_register_model_with_model_repack_with_estimator(
framework="TENSORFLOW",
framework_version="2.9",
nearest_model_name="resnet50",
data_input_configuration='{"input_1":[1,224,224,3]}',
)

request_dicts = register_model.request_dicts()
Expand Down
4 changes: 0 additions & 4 deletions tests/unit/test_estimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3260,7 +3260,6 @@ def test_register_default_image_without_instance_type_args(sagemaker_session):
framework = "TENSORFLOW"
framework_version = "2.9"
nearest_model_name = "resnet50"
data_input_config = '{"input_1":[1,224,224,3]}'

estimator.register(
content_types=content_types,
Expand All @@ -3271,7 +3270,6 @@ def test_register_default_image_without_instance_type_args(sagemaker_session):
framework=framework,
framework_version=framework_version,
nearest_model_name=nearest_model_name,
data_input_configuration=data_input_config,
)
sagemaker_session.create_model.assert_not_called()

Expand Down Expand Up @@ -3319,7 +3317,6 @@ def test_register_inference_image(sagemaker_session):
framework = "TENSORFLOW"
framework_version = "2.9"
nearest_model_name = "resnet50"
data_input_config = '{"input_1":[1,224,224,3]}'
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Have atleast 1 new test where we check for data_input_config if not already present.

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It is already present in the existing test files.


estimator.register(
content_types=content_types,
Expand All @@ -3333,7 +3330,6 @@ def test_register_inference_image(sagemaker_session):
framework=framework,
framework_version=framework_version,
nearest_model_name=nearest_model_name,
data_input_configuration=data_input_config,
)
sagemaker_session.create_model.assert_not_called()

Expand Down