Harmonize BCELoss example to F.binary_cross_entropy (#95178)
About that line:
```
torch.empty(3).random_(2)
```
* Since BCE supports targets in the interval [0, 1], a better example is to sample from uniform(0, 1), using `rand`
* BCE supports multiple dimensions, and the example in `F.binary_cross_entropy` highlights it
* `rand` is more well known than `random_`, which is a bit obscure (`rand` is in the [Random Sampling section in the docs](https://pytorch.org/docs/stable/torch.html#random-sampling))
* Chaining `empty` and `random_` gives binary values as floats, which is a weird way to get that result
* Why do it in two steps when we have sampling functions that do it in a single step?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95178
Approved by: https://github.com/albanD, https://github.com/kit1980
