class_docstr: Naive experience buffer class. It stores experience.
  
  Args:
      sample_batch_size (int): Batch size when sampling.
      limit (int, optional): Limit of number of experience samples. A number <= 0 means unlimited. Defaults to 0.
      cpu_offload (bool, optional): Whether to offload experience to cpu when sampling. Defaults to True.
code: def __init__(
      self,
      sample_batch_size: int,
      limit: int = 0,
      cpu_offload: bool = True,
  ) -> None:
      super().__init__(sample_batch_size, limit)
      self.cpu_offload = cpu_offload
      self.target_device = torch.device(
          f"cuda:{torch.cuda.current_device()}"
      )
      # TODO(ver217): add prefetch
      self.items: List[BufferItem] = []
  
file_path: ColossalAI/applications/Chat/coati/experience_buffer/naive.py
imports: import random
  import warnings
  from typing import List
  import torch
  from coati.experience_maker.base import Experience
  from .base import ExperienceBuffer
  from .utils import BufferItem, make_experience_batch, split_experience_batch
label_desc: Use image node_id 1 to create a new NaiveExperienceBuffer object from inherited base classes: ExperienceBuffer with example: obj = NaiveExperienceBuffer(sample_batch_size, limit, cpu_offload)