Different behavior in torch.full: checks if `fill_value` can be cast to `dtype`.

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## 🐛 Bug

The check function in https://github.com/Lightning-AI/lightning-thunder/blob/019557e1cbd2944a4d8d719954ee8a7c295c539b/thunder/core/prims.py#L2650-L2655 is not the same as the one used in `torch.full` (https://github.com/pytorch/pytorch/blob/f5e704a6f25939478f770f8980c344ab461f0113/c10/util/Half.h#L462)

### To Reproduce
An example of inconsistency:
```
import torch
import thunder

def func():
return torch.full((1,), 0.5, device = "cuda", dtype=torch.bool)
o =func()
print(o)

jfunc = thunder.jit(func)
o1=jfunc()
print(o1)
```
Torch outputs: `tensor([True], device='cuda:0')`
Thunder throws error `RuntimeError: Can't safely cast fill_value of numbertype to dtype thunder.dtypes.bool8`

### Expected behavior
Expect Thunder to behave the same as Torch
```
>>> torch.full((2,2),0.5,dtype=torch.bool)
tensor([[True, True],
[True, True]])
>>> torch.full((2,2),0.5,dtype=torch.int)
tensor([[0, 0],
[0, 0]], dtype=torch.int32)
>>> torch.full((2,2),-1,dtype=torch.uint32)
tensor([[4294967295, 4294967295],
[4294967295, 4294967295]], dtype=torch.uint32)
>>> torch.full((2,2),sys.maxsize,dtype=torch.uint32)
Traceback (most recent call last):
File "", line 1, in
RuntimeError: value cannot be converted to type uint32_t without overflow
>>> x=torch.full((1,2), 1j, dtype=torch.float)
Traceback (most recent call last):
File "", line 1, in
RuntimeError: value cannot be converted to type float without overflow
```

### Additional context

As a follow-up to https://github.com/Lightning-AI/lightning-thunder/pull/949

cc @apaz-cli

Start in thunder/core/prims.py around lines 2650-2655 and compare its fill_value casting check with the referenced PyTorch Half.h implementation used by torch.full. Reproduce the examples with torch.full and thunder.jit, especially bool, integer, unsigned integer, boundary, and complex values. Done means Thunder matches Torch's accepted conversions and overflow errors.

Written by the indexing model from the issue text.