[feature request] Indexing with boolean masks

## 🚀 Feature

No indexing with boolean mask, for example:

```python
import torch; import thunder
m = x <= 0.5

def f(x, m):
return x[m]


jf = thunder.jit(f)
jf(x, m)
```

fails with
```
RuntimeError: Advanced indexing currently only supports zero or one-dimensional integer tensors, but found a tensor with dtype bool8 and 1 dimensions

```

cc @apaz-cli

Start by running the provided Python reproducer with PyTorch and Thunder, then trace the advanced-indexing path that raises the boolean-tensor error. Done means the jitted function accepts x[m] when m is a boolean mask and no longer raises this runtime error.

Written by the indexing model from the issue text.