docstr: Copy data slice to the memory space indexed by the input tensor in the chunk.
  
  Args:
      tensor (torch.Tensor): the tensor used to retrieve meta information
      data_slice (torch.Tensor): the tensor to be copied to the chunk
docstr_tok: ["Copy","data","slice","to","the","memory","space","indexed","by","the","input","tensor","in","the","chunk",".","Args",":","tensor","(","torch.Tensor",")",":","the","tensor","used","to","retrieve","meta","information","data_slice","(","torch.Tensor",")",":","the","tensor","to","be","copied","to","the","chunk"]
code: def copy_tensor_to_chunk_slice(
      self,
      tensor: torch.Tensor,
      data_slice: torch.Tensor,
      update_ptr: bool = True,
  ) -> None:
      """
      Copy data slice to the memory space indexed by the input tensor in the chunk.
  
      Args:
          tensor (torch.Tensor): the tensor used to retrieve meta information
          data_slice (torch.Tensor): the tensor to be copied to the chunk
      """
      # sanity check
      assert self.is_gathered
  
      tensor_info = self.tensors_info[tensor]
      self.cuda_global_chunk[
          tensor_info.offset : tensor_info.end
      ].copy_(data_slice.data.flatten())
      if update_ptr:
          tensor.data = self.cuda_global_chunk[
              tensor_info.offset : tensor_info.end
          ].view(tensor.shape)
  
imports: from dataclasses import dataclass
  from enum import Enum
  from typing import Dict, List, Optional
  import torch
  import torch.distributed
  from torch.distributed import ProcessGroup
  from colossalai.utils import get_current_device
  from colossalai.utils.device import IS_NPU_AVAILABLE
label_desc: Use image node_id 18 for calling the Chunk obj's underlying member method code with example usage: obj.copy_tensor_to_chunk_slice(tensor, data_slice, update_ptr) without return types