class_docstr: Float16 optimizer for fp16 and bf16 data types.
  
  Args:
      optimizer (torch.optim.Optimizer): base optimizer such as Adam or SGD
      grad_scaler (BaseGradScaler): grad scaler for gradient chose in
                                    ``constant_grad_scaler`` or ``dynamic_grad_scaler``.
      clip_grad_norm (float, optional): clip gradients with this global L2 norm. Default 0.
                      Note that clipping is ignored if clip_grad == 0
      verbose (bool, optional): if set to `True`, will print debug info. Default False.
code: def _set_state(self, value):
      self._optimizer.state = value
  
imports: import torch
  import torch.distributed
  from torch.distributed import ProcessGroup
  from torch.optim import Optimizer
  from colossalai.amp.naive_amp.grad_scaler import BaseGradScaler
  from colossalai.kernel.op_builder import FusedOptimBuilder
  from colossalai.legacy.context import ParallelMode
  from colossalai.legacy.core import global_context
  from colossalai.legacy.utils import clip_grad_norm_fp32, copy_tensor_parallel_attributes
  from colossalai.logging import get_dist_logger
  from colossalai.utils import multi_tensor_applier
  from ._utils import has_inf_or_nan, zero_gard_by_list
label_desc: Use image node_id 19 for calling the FP16Optimizer obj's underlying member method code with example usage: obj._set_state(value) without return types