class_docstr: Tracker for the cuda RNG states.
  
  Using the `add` method, a cuda rng state is initialized based on
  the input `seed` and is assigned to `name`. Later, by forking the
  rng state, we can perform operations and return to our starting
  cuda state.
class_docstr_tok: ["Tracker","for","the","cuda","RNG","states",".","Using","the","`","add","`","method",",","a","cuda","rng","state","is","initialized","based","on","the","input","`","seed","`","and","is","assigned","to","`","name","`",".","Later",",","by","forking","the","rng","state",",","we","can","perform","operations","and","return","to","our","starting","cuda","state","."]
docstr: Set the rng states. For efficiency purposes, we do not check
  the size of seed for compatibility.
docstr_tok: ["Set","the","rng","states",".","For","efficiency","purposes",",","we","do","not","check","the","size","of","seed","for","compatibility","."]
code: def set_states(self, states):
      """Set the rng states. For efficiency purposes, we do not check
      the size of seed for compatibility."""
      self.states_ = states
  
imports: import copy
  import torch
  import contextlib
  from deepspeed import comm
  import weakref
  import mmap
  from torch import _C
  from deepspeed.runtime.config import DeepSpeedConfig
  from deepspeed.utils import logger
  from deepspeed.runtime.utils import copy_to_device, move_to_device, see_memory_usage, bwc_tensor_model_parallel_rank
  from deepspeed.utils.timer import SynchronizedWallClockTimer, FORWARD_GLOBAL_TIMER
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 4 for calling the CudaRNGStatesTracker obj's underlying member method code with example usage: obj.set_states(states) without return types