import onnx
from onnx import numpy_helper
import numpy as np
import onnxruntime
import onnxscript
from onnxscript import opset17 as op

@onnxscript.script()
def repro(x: onnxscript.FLOAT):
    y_scale = op.Constant(value_float=1.0)
    y_zero_point = op.Constant(
        value=numpy_helper.from_array(np.array(1, dtype=np.uint8))
    )
    return op.QuantizeLinear(x, y_scale, y_zero_point), y_scale, y_zero_point

model: onnx.ModelProto = repro.to_model_proto()
onnx.save(model, "model.onnx")

session = onnxruntime.InferenceSession("model.onnx")
x = np.array([1.0, 2.0], dtype=np.float32)
print(session.run(None, {"x": x}))

""" ORT 1.14
2023-01-30 16:36:46.616346569 [W:onnxruntime:, execution_frame.cc:835 VerifyOutputSizes] Expected shape from model of {} does not match actual shape of {2} for output return_val0
[array([2, 3], dtype=uint8), None, array(1, dtype=uint8)]
"""

""" ORT 1.13
2023-01-30 16:36:27.314479278 [W:onnxruntime:, execution_frame.cc:828 VerifyOutputSizes] Expected shape from model of {} does not match actual shape of {2} for output return_val0
[array([2, 3], dtype=uint8), array(1., dtype=float32), array(1, dtype=uint8)]
"""