def test_update_inference_tags_with_jumpstart_training_model_tags_inference():
random_tag_1 = {"Key": "tag-key-1", "Value": "tag-val-1"}
random_tag_2 = {"Key": "tag-key-2", "Value": "tag-val-2"}
js_tag = {
"Key": JumpStartTag.INFERENCE_MODEL_URI.value,
"Value": "garbage-value"
}
js_tag_2 = {
"Key": JumpStartTag.INFERENCE_MODEL_URI.value,
"Value": "garbage-value-2"
}
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=None)
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=[])
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=[random_tag_1])
assert [random_tag_2, js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2],
training_tags=[random_tag_1, js_tag])
assert [random_tag_2, js_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2, js_tag_2],
training_tags=[random_tag_1, js_tag])
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=None)
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[])
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[random_tag_1])
assert [js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[random_tag_1, js_tag])
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=None)
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[])
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[random_tag_1])
assert [js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[random_tag_1, js_tag])
def test_update_inference_tags_with_jumpstart_training_script_tags():
random_tag_1 = {"Key": "tag-key-1", "Value": "tag-val-1"}
random_tag_2 = {"Key": "tag-key-2", "Value": "tag-val-2"}
js_tag = {
"Key": JumpStartTag.TRAINING_SCRIPT_URI.value,
"Value": "garbage-value"
}
js_tag_2 = {
"Key": JumpStartTag.TRAINING_SCRIPT_URI.value,
"Value": "garbage-value-2"
}
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=None)
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=[])
assert [random_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2], training_tags=[random_tag_1])
assert [random_tag_2, js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2],
training_tags=[random_tag_1, js_tag])
assert [random_tag_2, js_tag_2
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[random_tag_2, js_tag_2],
training_tags=[random_tag_1, js_tag])
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=None)
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[])
assert [] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[random_tag_1])
assert [js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=[], training_tags=[random_tag_1, js_tag])
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=None)
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[])
assert None is utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[random_tag_1])
assert [js_tag
] == utils.update_inference_tags_with_jumpstart_training_tags(
inference_tags=None, training_tags=[random_tag_1, js_tag])