def test_custom_scaler_pipeline_left(self):
pipe = make_pipeline(
CustomOpTransformer(op_version=TARGET_OPSET),
StandardScaler())
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
matf = mat.astype(np.float32)
try:
model_onnx = to_onnx(pipe, matf, target_opset=TARGET_OPSET)
except RuntimeError as e:
assert "cannot be infered" in str(e)
pipe = make_pipeline(
CustomOpTransformerShape(op_version=TARGET_OPSET),
StandardScaler())
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
assert z is not None
matf = mat.astype(np.float32)
model_onnx = to_onnx(pipe, matf)
# Next instructions fails...
# Field 'shape' of type is required but missing.
# onnx.checker.check_model(model_onnx)
dump_data_and_model(
mat.astype(np.float32), pipe, model_onnx,
basename="CustomTransformerPipelineLeftAlgebra")
def test_custom_scaler_pipeline_left(self):
pipe = make_pipeline(
CustomOpTransformer(op_version=TARGET_OPSET),
StandardScaler())
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
matf = mat.astype(np.float32)
try:
model_onnx = to_onnx(pipe, matf, target_opset=TARGET_OPSET)
except RuntimeError as e:
assert "inputs should contain one name" in str(e)
pipe = make_pipeline(
CustomOpTransformerShape(op_version=TARGET_OPSET),
StandardScaler())
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
assert z is not None
matf = mat.astype(np.float32)
model_onnx = to_onnx(pipe, matf, target_opset=TARGET_OPSET)
if StrictVersion(onnx.__version__) >= StrictVersion("1.8.0"):
# It fails for older version of onnx.
onnx.checker.check_model(model_onnx)
dump_data_and_model(
mat.astype(np.float32), pipe, model_onnx,
basename="CustomTransformerPipelineLeftAlgebra")
def test_custom_scaler_pipeline_right(self):
pipe = make_pipeline(
StandardScaler(),
CustomOpTransformerShape(op_version=TARGET_OPSET))
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
assert z is not None
matf = mat.astype(np.float32)
model_onnx = to_onnx(pipe, matf, target_opset=TARGET_OPSET)
onnx.checker.check_model(model_onnx)
dump_data_and_model(
mat.astype(np.float32), pipe, model_onnx,
basename="CustomTransformerPipelineRightAlgebra")
def test_custom_scaler_pipeline_right(self):
pipe = make_pipeline(StandardScaler(), CustomOpTransformerShape())
mat = np.array([[0., 1.], [0., 1.], [2., 2.]])
pipe.fit(mat)
z = pipe.transform(mat)
assert z is not None
matf = mat.astype(np.float32)
model_onnx = to_onnx(pipe, matf)
# Next instructions fails...
# Field 'shape' of type is required but missing.
# onnx.checker.check_model(model_onnx)
# use assert_consistent_outputs
# calls dump_data_and_model
dump_data_and_model(
mat.astype(np.float32), pipe, model_onnx,
basename="CustomTransformerPipelineRightAlgebra")
