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16 | 16 | from sagemaker import hyperparameters, image_uris, model_uris, script_uris |
17 | 17 | from sagemaker.estimator import Estimator |
18 | 18 | from sagemaker.jumpstart.constants import ( |
19 | | - INFERENCE_ENTRYPOINT_SCRIPT_NAME, |
| 19 | + INFERENCE_ENTRY_POINT_SCRIPT_NAME, |
20 | 20 | JUMPSTART_DEFAULT_REGION_NAME, |
21 | | - TRAINING_ENTRYPOINT_SCRIPT_NAME, |
| 21 | + TRAINING_ENTRY_POINT_SCRIPT_NAME, |
22 | 22 | ) |
23 | 23 | from sagemaker.jumpstart.utils import get_jumpstart_content_bucket |
24 | 24 | from sagemaker.utils import name_from_base |
@@ -70,7 +70,7 @@ def test_jumpstart_transfer_learning_estimator_class(setup): |
70 | 70 | image_uri=image_uri, |
71 | 71 | source_dir=script_uri, |
72 | 72 | model_uri=model_uri, |
73 | | - entry_point=TRAINING_ENTRYPOINT_SCRIPT_NAME, |
| 73 | + entry_point=TRAINING_ENTRY_POINT_SCRIPT_NAME, |
74 | 74 | role=get_sm_session().get_caller_identity_arn(), |
75 | 75 | sagemaker_session=get_sm_session(), |
76 | 76 | enable_network_isolation=True, |
@@ -111,7 +111,7 @@ def test_jumpstart_transfer_learning_estimator_class(setup): |
111 | 111 | estimator.deploy( |
112 | 112 | initial_instance_count=instance_count, |
113 | 113 | instance_type=inference_instance_type, |
114 | | - entry_point=INFERENCE_ENTRYPOINT_SCRIPT_NAME, |
| 114 | + entry_point=INFERENCE_ENTRY_POINT_SCRIPT_NAME, |
115 | 115 | image_uri=image_uri, |
116 | 116 | source_dir=script_uri, |
117 | 117 | endpoint_name=endpoint_name, |
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