LayerNormalization without bias throws segfault

[ex3ndr]

Describe the issue

LayerNormalization without bias throws segfault after exporting from PyTorch, all tools report correct graphs and it looks like the bug is in runtime

To reproduce

import torch
from torch import nn
class ONNXBug(nn.Module):
    def __init__(self):
        super().__init__()
        self.ln = nn.LayerNorm(10, bias=False)
    def forward(self, x):
        return self.ln(x)
model = ONNXBug()
dummy = torch.zeros(10).unsqueeze(0)
torch.onnx.export(model, dummy, "test.onnx", export_params=True, input_names = ['input'], output_names = ['output'])
import onnxruntime as rt
sess = rt.InferenceSession("./test.onnx")

Urgency

No response

Platform

Mac

OS Version

14.2.1

ONNX Runtime Installation

Released Package

ONNX Runtime Version or Commit ID

I have tried most recent versions starting from 1.15

ONNX Runtime API

Python

Architecture

X64

Execution Provider

Default CPU, CUDA, TensorRT

Execution Provider Library Version

12.1

[wschin]

This should have fixed in latest main commit. I run you script and hit no error. Please install nightly from https://onnxruntime.ai/docs/install/. Please feel free to re-open if the error still exists.