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fix: HuggingFaceProcessor parameterized instance_type when image_uri is absent #4072

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Merged
merged 1 commit into from
Aug 29, 2023
Merged

fix: HuggingFaceProcessor parameterized instance_type when image_uri is absent #4072

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1 change: 1 addition & 0 deletions src/sagemaker/image_uris.py
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Original file line number Diff line number Diff line change
Expand Up @@ -619,6 +619,7 @@ def _format_tag(tag_prefix, processor, py_version, container_version, inference_
return "-".join(x for x in (tag_prefix, processor, py_version, container_version) if x)


@override_pipeline_parameter_var
def get_training_image_uri(
region,
framework,
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6 changes: 4 additions & 2 deletions src/sagemaker/workflow/utilities.py
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Expand Up @@ -390,8 +390,10 @@ def override_pipeline_parameter_var(func):
We should remove this decorator after the grace period.
"""
warning_msg_template = (
"The input argument %s of function (%s) is a pipeline variable (%s), which is not allowed. "
"The default_value of this Parameter object will be used to override it. "
"The input argument %s of function (%s) is a pipeline variable (%s), "
"which is interpreted in pipeline execution time only. "
"As the function needs to evaluate the argument value in SDK compile time, "
"the default_value of this Parameter object will be used to override it. "
"Please make sure the default_value is valid."
)

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17 changes: 16 additions & 1 deletion tests/unit/sagemaker/workflow/test_processing_step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,6 +69,7 @@
from tests.unit import DATA_DIR
from tests.unit.sagemaker.workflow.conftest import ROLE, BUCKET, IMAGE_URI, INSTANCE_TYPE

HF_INSTANCE_TYPE = "ml.p3.2xlarge"
DUMMY_S3_SCRIPT_PATH = "s3://dummy-s3/dummy_script.py"
LOCAL_SCRIPT_PATH = os.path.join(DATA_DIR, "workflow/abalone/preprocessing.py")
SPARK_APP_JAR_PATH = os.path.join(
Expand Down Expand Up @@ -142,7 +143,7 @@
pytorch_version="1.7",
role=ROLE,
instance_count=1,
instance_type="ml.p3.2xlarge",
instance_type=HF_INSTANCE_TYPE,
),
{"code": DUMMY_S3_SCRIPT_PATH},
),
Expand Down Expand Up @@ -446,8 +447,15 @@ def test_processing_step_with_framework_processor(
):

processor, run_inputs = framework_processor
default_instance_type = (
HF_INSTANCE_TYPE if type(processor) is HuggingFaceProcessor else INSTANCE_TYPE
)
instance_type_param = ParameterString(
name="ProcessingInstanceType", default_value=default_instance_type
)
processor.sagemaker_session = pipeline_session
processor.role = ROLE
processor.instance_type = instance_type_param

processor.volume_kms_key = "volume-kms-key"
processor.network_config = network_config
Expand All @@ -465,6 +473,7 @@ def test_processing_step_with_framework_processor(
name="MyPipeline",
steps=[step],
sagemaker_session=pipeline_session,
parameters=[instance_type_param],
)

step_args = get_step_args_helper(step_args, "Processing")
Expand All @@ -475,6 +484,12 @@ def test_processing_step_with_framework_processor(
step_args["ProcessingOutputConfig"]["Outputs"][0]["S3Output"]["S3Uri"]
== processing_output.destination
)
assert (
type(step_args["ProcessingResources"]["ClusterConfig"]["InstanceType"]) is ParameterString
)
step_args["ProcessingResources"]["ClusterConfig"]["InstanceType"] = step_args[
"ProcessingResources"
]["ClusterConfig"]["InstanceType"].expr

del step_args["ProcessingInputs"][0]["S3Input"]["S3Uri"]
del step_def["Arguments"]["ProcessingInputs"][0]["S3Input"]["S3Uri"]
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