def test_jumpstart_cache_get_specs():
cache = JumpStartModelsCache(s3_bucket_name="some_bucket")
model_id, version = "tensorflow-ic-imagenet-inception-v3-classification-4", "2.0.0"
assert get_spec_from_base_spec(model_id=model_id, version=version) == cache.get_specs(
model_id=model_id, semantic_version_str=version
)
model_id = "tensorflow-ic-imagenet-inception-v3-classification-4"
assert get_spec_from_base_spec(model_id=model_id, version="2.0.0") == cache.get_specs(
model_id=model_id, semantic_version_str="2.0.*"
)
model_id, version = "tensorflow-ic-imagenet-inception-v3-classification-4", "1.0.0"
assert get_spec_from_base_spec(model_id=model_id, version=version) == cache.get_specs(
model_id=model_id, semantic_version_str=version
)
model_id = "pytorch-ic-imagenet-inception-v3-classification-4"
assert get_spec_from_base_spec(model_id=model_id, version="1.0.0") == cache.get_specs(
model_id=model_id, semantic_version_str="1.*"
)
model_id = "pytorch-ic-imagenet-inception-v3-classification-4"
assert get_spec_from_base_spec(model_id=model_id, version="1.0.0") == cache.get_specs(
model_id=model_id, semantic_version_str="1.0.*"
)
with pytest.raises(KeyError):
cache.get_specs(model_id=model_id + "bak", semantic_version_str="*")
with pytest.raises(KeyError):
cache.get_specs(model_id=model_id, semantic_version_str="9.*")
with pytest.raises(KeyError):
cache.get_specs(model_id=model_id, semantic_version_str="BAD")
with pytest.raises(KeyError):
cache.get_specs(
model_id=model_id,
semantic_version_str="2.1.*",
)
with pytest.raises(KeyError):
cache.get_specs(
model_id=model_id,
semantic_version_str="3.9.*",
)
with pytest.raises(KeyError):
cache.get_specs(
model_id=model_id,
semantic_version_str="5.*",
)
def add_options_to_hyperparameter(*largs, **kwargs):
spec = get_spec_from_base_spec(*largs, **kwargs)
spec.hyperparameters.append(
JumpStartHyperparameter({
"name":
"penalty",
"type":
"text",
"default":
"l2",
"options": ["l1", "l2", "elasticnet", "none"],
"scope":
"algorithm",
}))
return spec
def test_jumpstart_models_cache_get_fxs():
assert get_header_from_base_header(
region="us-west-2", model_id="pytorch-ic-mobilenet-v2",
version="*") == accessors.JumpStartModelsAccessor.get_model_header(
region="us-west-2",
model_id="pytorch-ic-mobilenet-v2",
version="*")
assert get_spec_from_base_spec(
region="us-west-2", model_id="pytorch-ic-mobilenet-v2",
version="*") == accessors.JumpStartModelsAccessor.get_model_specs(
region="us-west-2",
model_id="pytorch-ic-mobilenet-v2",
version="*")
# necessary because accessors is a static module
reload(accessors)
def add_options_to_hyperparameter(*largs, **kwargs):
spec = get_spec_from_base_spec(*largs, **kwargs)
spec.hyperparameters.extend([
JumpStartHyperparameter({
"name":
"penalty",
"type":
"text",
"default":
"l2",
"options": ["l1", "l2", "elasticnet", "none"],
"scope":
"algorithm",
}),
JumpStartHyperparameter({
"name": "test_bool_param",
"type": "bool",
"default": True,
"scope": "algorithm",
}),
JumpStartHyperparameter({
"name": "test_exclusive_min_param",
"type": "float",
"default": 4,
"scope": "algorithm",
"exclusive_min": 1,
}),
JumpStartHyperparameter({
"name": "test_exclusive_max_param",
"type": "int",
"default": -4,
"scope": "algorithm",
"exclusive_max": 4,
}),
JumpStartHyperparameter({
"name": "test_exclusive_min_param_text",
"type": "text",
"default": "hello",
"scope": "algorithm",
"exclusive_min": 1,
}),
JumpStartHyperparameter({
"name": "test_exclusive_max_param_text",
"type": "text",
"default": "hello",
"scope": "algorithm",
"exclusive_max": 6,
}),
JumpStartHyperparameter({
"name": "test_min_param_text",
"type": "text",
"default": "hello",
"scope": "algorithm",
"min": 1,
}),
JumpStartHyperparameter({
"name": "test_max_param_text",
"type": "text",
"default": "hello",
"scope": "algorithm",
"max": 6,
}),
])
return spec
def make_deprecated_spec(*largs, **kwargs):
spec = get_spec_from_base_spec(*largs, **kwargs)
spec.deprecated = True
return spec
def make_vulnerable_training_spec(*largs, **kwargs):
spec = get_spec_from_base_spec(*largs, **kwargs)
spec.training_vulnerable = True
spec.training_vulnerabilities = ["some", "vulnerability"]
return spec
def make_vulnerable_inference_spec(*largs, **kwargs):
spec = get_spec_from_base_spec(*largs, **kwargs)
spec.inference_vulnerable = True
spec.inference_vulnerabilities = ["some", "vulnerability"]
return spec