Partial function is not supported in `grad_transform`

## 🚀 Feature

Hitting this assert below vvv
```py
root@847841b8737c:/opt/pytorch/lightning-thunder# python /volume/pooling.py
Traceback (most recent call last):
File "/volume/pooling.py", line 36, in
o = jit_model(image)
File "/opt/pytorch/lightning-thunder/thunder/__init__.py", line 632, in fn_
cache_entry, inps, pro_to_epi = get_computation_and_inputs(*args, **kwargs)
File "/opt/pytorch/lightning-thunder/thunder/__init__.py", line 265, in cache_info_wrapper
res = fn(*args, **kwargs)
File "/opt/pytorch/lightning-thunder/thunder/__init__.py", line 574, in get_computation_and_inputs
computation_trc, backward_trc = split_forward_backward(computation_trc, cd, cs, *inps)
File "/opt/pytorch/lightning-thunder/thunder/executors/torch_autograd.py", line 216, in split_forward_backward
fw_trace, bw_trace = forward_and_backward_from_trace(primal_trace, torch_autograd=True)
File "/opt/pytorch/lightning-thunder/thunder/core/transforms.py", line 3879, in forward_and_backward_from_trace
forward_trace = construct_trace()(augmented_forward_fn, *trace.args, **trace.kwargs)
File "/opt/pytorch/lightning-thunder/thunder/core/interpreter.py", line 1292, in fn_
return fn(*args, **kwargs)
File "/opt/pytorch/lightning-thunder/thunder/common.py", line 528, in _trace
result = fn(*proxyargs, **proxykwargs)
File "/opt/pytorch/lightning-thunder/thunder/core/transforms.py", line 3850, in augmented_forward_fn
result, env = augmented_forward_pass(*args, trace=trace, **kwargs)
File "/opt/pytorch/lightning-thunder/thunder/core/transforms.py", line 3461, in augmented_forward_pass
result, env = eval_trace(
File "/opt/pytorch/lightning-thunder/thunder/core/transforms.py", line 1698, in eval_trace
prim_func = symbol_mapper(symbol)
File "/opt/pytorch/lightning-thunder/thunder/core/transforms.py", line 3385, in vjp_symbol_mapper
vjp_impl, backward_fn = make_aug_forward_and_backward(symbol)
File "/opt/pytorch/lightning-thunder/thunder/core/vjp_utils.py", line 63, in make_aug_forward_and_backward
joint_trace = thunder.trace(inline_trace=False, use_dce=False)(joint_forward_backward, *bsym.args, **bsym.kwargs)
File "/opt/pytorch/lightning-thunder/thunder/core/interpreter.py", line 1292, in fn_
return fn(*args, **kwargs)
File "/opt/pytorch/lightning-thunder/thunder/common.py", line 506, in _trace
proxyargs, proxykwargs = _unpack_inputs(fn, trace, args, kwargs, rename_proxies=rename_proxies)
File "/opt/pytorch/lightning-thunder/thunder/common.py", line 273, in _unpack_inputs
si = get_siginfo(fn, args, kwargs)
File "/opt/pytorch/lightning-thunder/thunder/core/codeutils.py", line 313, in get_siginfo
check(
File "/opt/pytorch/lightning-thunder/thunder/core/baseutils.py", line 103, in check
raise exception_type(s())
NotImplementedError: Support for partials with positional args (like ('test',)) is not implemented yet
```

I was trying to use something like
```py
foo = partial(bar, pos_arg0)
OperatorExecutor.register_operator(..., grad_transform=fn)
```

This isn't a high priority issue, since we can easily work around it for now. Filing the issue just to keep track of missing feature.

Start in thunder/core/codeutils.py at get_siginfo, where the traceback reports positional partial arguments as unsupported. Trace how this is reached from thunder/core/vjp_utils.py through make_aug_forward_and_backward, reproducing the case with the reported pooling.py script. Done means grad_transform accepts a partial with positional arguments without raising this NotImplementedError.

Written by the indexing model from the issue text.