def test_model_metadata():
meta = ModelMetadataValidator(
name="model-name",
versions=["model-version"],
platform="platform-name",
inputs=[
MetadataTensorValidator(name="input-name",
datatype="input-type",
shape=[1, 2])
],
outputs=[
MetadataTensorValidator(name="output-name",
datatype="output-type",
shape=[1, 2])
],
)
assert meta.to_dict() == {
"name":
"model-name",
"versions": ["model-version"],
"platform":
"platform-name",
"inputs": [{
"name": "input-name",
"datatype": "input-type",
"shape": [1, 2]
}],
"outputs": [{
"name": "output-name",
"datatype": "output-type",
"shape": [1, 2]
}],
}
def test_model_metadata_wrong_inputs_outputs(invalid_tensor):
with pytest.raises(SeldonInvalidMetadataError):
meta = ModelMetadataValidator(inputs=invalid_tensor)
with pytest.raises(SeldonInvalidMetadataError):
meta = ModelMetadataValidator(outputs=invalid_tensor)
def test_model_metadata_wrong_versions(invalid_versions):
with pytest.raises(SeldonInvalidMetadataError):
meta = ModelMetadataValidator(versions=invalid_versions)