CoreML ignores alpha in torch.add/torch.sub and gives incorrect output

[metascroy]

🐞Describing the bug

CoreML ignores the alpha parameter in torch.add/torch.sub and gives incorrect output.

To Reproduce

import torch

class Model(torch.nn.Module):
    def forward(self, x, y):
        return torch.sub(x, y, alpha=5)

model = Model()
inputs = (
    5 * torch.ones(10),
    2 * torch.ones(10),
)

ep = torch.export.export(model.eval(), inputs)

import coremltools as ct
import numpy as np
ep = ep.run_decompositions({})

eager_outputs = model(*inputs)

mlmodel = ct.convert(ep)

coreml_inputs = mlmodel.get_spec().description.input
coreml_outputs = mlmodel.get_spec().description.output
predict_inputs = {str(ct_in.name): pt_in.detach().cpu().numpy().astype(np.int32) for ct_in, pt_in in zip(coreml_inputs, inputs)}
out = mlmodel.predict(predict_inputs)

print("Eager", eager_outputs)
print("CoremL", out)

The outputs are:

Eager tensor([-5., -5., -5., -5., -5., -5., -5., -5., -5., -5.])
CoremL {'sub': array([3., 3., 3., 3., 3., 3., 3., 3., 3., 3.], dtype=float32)}

CoreML is ignoring the alpha parameter.

System environment (please complete the following information):

• coremltools version: 8.3
• OS (e.g. MacOS version or Linux type): macOS15