def test_model_signature():
signature1 = ModelSignature(inputs=Schema(
[ColSpec(DataType.boolean),
ColSpec(DataType.binary)]),
outputs=Schema([
ColSpec(name=None, type=DataType.double),
ColSpec(name=None, type=DataType.double)
]))
signature2 = ModelSignature(inputs=Schema(
[ColSpec(DataType.boolean),
ColSpec(DataType.binary)]),
outputs=Schema([
ColSpec(name=None, type=DataType.double),
ColSpec(name=None, type=DataType.double)
]))
assert signature1 == signature2
signature3 = ModelSignature(inputs=Schema(
[ColSpec(DataType.boolean),
ColSpec(DataType.binary)]),
outputs=Schema([
ColSpec(name=None, type=DataType.float),
ColSpec(name=None, type=DataType.double)
]))
assert signature3 != signature1
as_json = json.dumps(signature1.to_dict())
signature4 = ModelSignature.from_dict(json.loads(as_json))
assert signature1 == signature4
signature5 = ModelSignature(inputs=Schema(
[ColSpec(DataType.boolean),
ColSpec(DataType.binary)]),
outputs=None)
as_json = json.dumps(signature5.to_dict())
signature6 = ModelSignature.from_dict(json.loads(as_json))
assert signature5 == signature6
def test_model_signature_with_tensorspec():
signature1 = ModelSignature(
inputs=Schema([TensorSpec(np.dtype("float"), (-1, 28, 28))]),
outputs=Schema([TensorSpec(np.dtype("float"), (-1, 10))]),
)
signature2 = ModelSignature(
inputs=Schema([TensorSpec(np.dtype("float"), (-1, 28, 28))]),
outputs=Schema([TensorSpec(np.dtype("float"), (-1, 10))]),
)
# Single type mismatch
assert signature1 == signature2
signature3 = ModelSignature(
inputs=Schema([TensorSpec(np.dtype("float"), (-1, 28, 28))]),
outputs=Schema([TensorSpec(np.dtype("int"), (-1, 10))]),
)
assert signature3 != signature1
# Name mismatch
signature4 = ModelSignature(
inputs=Schema([TensorSpec(np.dtype("float"), (-1, 28, 28))]),
outputs=Schema([TensorSpec(np.dtype("float"), (-1, 10), "misMatch")]),
)
assert signature3 != signature4
as_json = json.dumps(signature1.to_dict())
signature5 = ModelSignature.from_dict(json.loads(as_json))
assert signature1 == signature5
# Test with name
signature6 = ModelSignature(
inputs=Schema(
[
TensorSpec(np.dtype("float"), (-1, 28, 28), name="image"),
TensorSpec(np.dtype("int"), (-1, 10), name="metadata"),
]
),
outputs=Schema([TensorSpec(np.dtype("float"), (-1, 10), name="outputs")]),
)
signature7 = ModelSignature(
inputs=Schema(
[
TensorSpec(np.dtype("float"), (-1, 28, 28), name="image"),
TensorSpec(np.dtype("int"), (-1, 10), name="metadata"),
]
),
outputs=Schema([TensorSpec(np.dtype("float"), (-1, 10), name="outputs")]),
)
assert signature6 == signature7
assert signature1 != signature6
# Test w/o output
signature8 = ModelSignature(
inputs=Schema([TensorSpec(np.dtype("float"), (-1, 28, 28))]), outputs=None
)
as_json = json.dumps(signature8.to_dict())
signature9 = ModelSignature.from_dict(json.loads(as_json))
assert signature8 == signature9
def from_dict(cls, model_dict):
"""Load a model from its YAML representation."""
if "signature" in model_dict and isinstance(model_dict["signature"], dict):
model_dict = model_dict.copy()
model_dict["signature"] = ModelSignature.from_dict(model_dict["signature"])
return cls(**model_dict)