[torchlib] Fix unbind.int if num_outputs=1 (#2684)

This fixes the issue of 
```
  return [op.Squeeze(out, [dim]) for out in outputs]
                                              ^^^^^^^
TypeError: 'SymbolicTensor' object is not iterable
```
when trying to export LSTM modules in `torch`.
This also already appeared in torch issues in
pytorch/pytorch#126339


The core seems to be the changes in #2597.
To my understanding the split returns a single `SymbolicTensor` instead
of a sequence when `dim=1`.
The fix implemented here is the casting of the return type to a list.


I struggled with writing a test that reproduces this nicely in here, any
guidance on that would be welcome.

---------

Co-authored-by: Justin Chu <[email protected]>

Author: sebimarkgraf

onnxscript/function_libs/torch_lib/ops/core.py

@@ -8957,7 +8957,12 @@ def aten_unbind(self: TTensor, dim: int = 0) -> Sequence[TTensor]:
     if isinstance(self.shape[dim], int) and not version_utils.torch_older_than("2.7"):
         # We can create a definitive split op if the input shape is static
         # Only torch>=2.7 supports correctly generating the correct number of outputs for Split
-        outputs = op.Split(self, axis=dim, num_outputs=self.shape[dim])
+        num_outputs = self.shape[dim]
+        if num_outputs != 1:
+            outputs = op.Split(self, axis=dim, num_outputs=num_outputs)
+        else:
+            outputs = [self]
+
         return [op.Squeeze(out, [dim]) for out in outputs]
 
     return op.SplitToSequence(self, axis=dim, keepdims=False)