import io
import torch
import torch.nn as nn
import onnxruntime as ort

class MWE(nn.Module):
    def __init__(self):
        super().__init__()
        self.conv = nn.Conv2d(1, 16, kernel_size=3, padding=1)
        self.bn   = nn.BatchNorm2d(16)

    def forward(self, x):
        f_1 = self.bn(self.conv(x[:, 0:1]))
        f_2 = self.bn(self.conv(x[:, 1:2]))
        return f_1 + f_2


model       = MWE().eval()
dummy_input = (torch.randn(1, 2, 2, 2),)
dummy_file  = io.BytesIO()

torch.onnx.export(
    model,
    dummy_input,
    dummy_file,
    dynamo=True,
    optimize=True,  # Issue is only with optimize set to `True`
    verify=True,    # Fails to `Execute the model with ONNX Runtime...`
)

dummy_file.seek(0)
# This yields an error
_ = ort.InferenceSession(dummy_file.getvalue())

---

(snip)
[torch.onnx] Obtain model graph for `MWE([...]` with `torch.export.export(..., strict=False)`... ✅
(snip)
[torch.onnx] Check the ONNX model... ✅
[torch.onnx] Execute the model with ONNX Runtime...
[torch.onnx] Execute the model with ONNX Runtime... ❌
(snip)
InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Invalid model. Node input 'conv.weight_1' is not a graph input, initializer, or output of a previous node.

---

torch==2.11.0
onnx==1.21.0
onnxscript==0.6.2
onnxruntime==1.24.4