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change: enable neo framework version support on ml_inf2 and ml_trn1 #3909

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Merged
merged 1 commit into from
Jun 7, 2023
Merged

change: enable neo framework version support on ml_inf2 and ml_trn1 #3909

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11 changes: 8 additions & 3 deletions src/sagemaker/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -844,15 +844,20 @@ def multi_version_compilation_supported(
):
if target_instance_type and framework and framework_version:
framework = framework.lower()

multi_version_frameworks_support_mapping = {
"inferentia": ["pytorch", "tensorflow", "mxnet"],
"ml_inf1": ["pytorch", "tensorflow", "mxnet"],
"ml_inf2": ["pytorch", "tensorflow"],
"ml_trn1": ["pytorch", "tensorflow"],
"neo_ioc_targets": ["pytorch", "tensorflow"],
"neo_edge_targets": ["pytorch", "tensorflow"],
}
if target_instance_type in NEO_IOC_TARGET_DEVICES:
return framework in multi_version_frameworks_support_mapping["neo_ioc_targets"]
if target_instance_type == "ml_inf1":
return framework in multi_version_frameworks_support_mapping["inferentia"]
if target_instance_type in ["ml_inf1", "ml_inf2", "ml_trn1"]:
return (
framework in multi_version_frameworks_support_mapping[target_instance_type]
)
if target_instance_type not in NEO_MULTIVERSION_UNSUPPORTED:
return framework in multi_version_frameworks_support_mapping["neo_edge_targets"]
return False
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68 changes: 22 additions & 46 deletions tests/unit/sagemaker/model/test_neo.py
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Expand Up @@ -362,59 +362,35 @@ def test_compile_with_tensorflow_neo_in_ml_inf(session):
)


def test_compile_validates_framework_version(sagemaker_session):
sagemaker_session.wait_for_compilation_job = Mock(
return_value={
"CompilationJobStatus": "Completed",
"ModelArtifacts": {"S3ModelArtifacts": "s3://output-path/model.tar.gz"},
"InferenceImage": None,
}
)
@pytest.mark.parametrize(
"target,framework,fx_version,expected_fx_version",
[
("ml_c4", "pytorch", "1.6", "1.6"),
("rasp3b", "pytorch", "1.6.1", "1.6"),
("amba_cv2", "pytorch", "1.6.1", None),
("ml_c4", "tensorflow", "1.15.1", "1.15"),
("ml_c4", "tensorflow", "2.15.1", "2.15"),
("ml_inf1", "tensorflow", "2.15.1", "2.15"),
("ml_inf2", "pytorch", "2.0", "2.0"),
("ml_inf2", "pytorch", "2.0.1", "2.0"),
("ml_trn1", "pytorch", "2.0.1", "2.0"),
("ml_trn1", "tensorflow", "2.0.1", "2.0"),
],
)
def test_compile_validates_framework_version(
sagemaker_session, target, framework, fx_version, expected_fx_version
):
model = _create_model(sagemaker_session)
model.compile(
target_instance_family="ml_c4",
input_shape={"data": [1, 3, 1024, 1024]},
output_path="s3://output",
role="role",
framework="pytorch",
framework_version="1.6.1",
job_name="compile-model",
)

assert model.image_uri is None

sagemaker_session.wait_for_compilation_job = Mock(
return_value={
"CompilationJobStatus": "Completed",
"ModelArtifacts": {"S3ModelArtifacts": "s3://output-path/model.tar.gz"},
"InferenceImage": None,
}
)

config = model._compilation_job_config(
"rasp3b",
{"data": [1, 3, 1024, 1024]},
"s3://output",
"role",
900,
"compile-model",
"pytorch",
None,
framework_version="1.6.1",
)

assert config["input_model_config"]["FrameworkVersion"] == "1.6"

config = model._compilation_job_config(
"amba_cv2",
target,
{"data": [1, 3, 1024, 1024]},
"s3://output",
"role",
900,
"compile-model",
"pytorch",
framework,
None,
framework_version="1.6.1",
framework_version=fx_version,
)

assert config["input_model_config"].get("FrameworkVersion", None) is None
assert config["input_model_config"].get("FrameworkVersion", None) == expected_fx_version