Support negative indices for pytorch.swapaxes

## 🌱 Describe your Feature Request
Please add support for negative indices in the Pytorch op `swapaxes`.

## How can this feature be used?
Swapaxes is a basic operation. Coremltools already supports it, but only with positive indices.

## Describe alternatives you've considered
- Use positive indices
- Use `transpose()`

## Additional context
Test code:

```python
import torch
import coremltools as ct

class MyModel(torch.nn.Module):
def __init__(self):
super().__init__()

def forward(self, x):
return x.swapaxes(-2, -1)

model = MyModel().eval()

with torch.inference_mode():
example_input = torch.rand(10, 20)
traced_model = torch.jit.trace(model, example_input)

coreml_model = ct.convert(
traced_model,
convert_to="neuralnetwork",
inputs=[ct.TensorType(shape=example_input.shape, name="x")],
debug=True,
)
```

Locate the PyTorch swapaxes conversion entry point and the existing handling for axis indices; use the supplied traced-model example as the starting reproduction. Done means conversion of swapaxes(-2, -1) succeeds for the shown input, with a regression test covering the behavior.

Written by the indexing model from the issue text.