[Bug] [Relax][ONNX] Min import fails on symbolic broadcast

### Expected behavior

The Relax ONNX frontend should import a valid ONNX Min with symbolic input shapes.

### Actual behavior

The script constructs a valid ONNX model. `onnx.checker.check_model` and ONNX Runtime session construction succeed. `from_onnx` fails while converting `Min`:

```text
Error converting operator Min, with inputs: [x, y]
Traceback (most recent call last):
...
File ".../python/tvm/relax/frontend/onnx/onnx_frontend.py", line 2420, in compute_broadcast_shape
target.append(max(ai, bi))
...
ValueError: Cannot use and / or / not operator to Expr, hint: use tvm.tirx.all / tvm.tirx.any, if it is None checking, use node is not None
```

### Environment

* OS: macOS 15.6 (Darwin 24.6.0, arm64)
* Python: 3.12.2
* TVM: c7b458e946bc4266915da582457476bdcd9705ae (tag v0.26.0; package reports 0.26.dev0)
* ONNX: 1.17.0
* ONNX Runtime: 1.21.1
* Frontend: `tvm.relax.frontend.onnx.from_onnx`

### Steps to reproduce

The following self-contained script constructs the model:

```python
#!/usr/bin/env python3
"""Reproduce the Relax ONNX symbolic-broadcast Min import failure."""

import onnx
import onnxruntime as ort
from onnx import TensorProto, helper
from tvm.relax.frontend.onnx import from_onnx

def main() -> None:
x = helper.make_tensor_value_info("x", TensorProto.FLOAT, ["n", 4])
y = helper.make_tensor_value_info("y", TensorProto.FLOAT, ["n", 4])
out = helper.make_tensor_value_info("out", TensorProto.FLOAT, ["n", 4])
graph = helper.make_graph(
[helper.make_node("Min", ["x", "y"], ["out"])],
"min_symbolic_broadcast",
[x, y],
[out],
)
model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 18)])

onnx.checker.check_model(model)
ort.InferenceSession(model.SerializeToString(), providers=["CPUExecutionProvider"])
from_onnx(model, opset=18, keep_params_in_input=True)

if __name__ == "__main__":
main()
```

### Analysis

`compute_broadcast_shape` uses Python `max` and boolean logic on input dimensions. When a dimension is a symbolic `tirx.Expr`, Python boolean conversion raises before a Relax graph is produced.

### Triage

* needs-triage

Start by running the self-contained reproduction and inspect compute_broadcast_shape in python/tvm/relax/frontend/onnx/onnx_frontend.py around line 2420, reached through tvm.relax.frontend.onnx.from_onnx. Done means the symbolic-shape Min model imports successfully without the Python Expr boolean-conversion error.

Written by the indexing model from the issue text.