class_docstr: Helper class to simplify the handling of parameter buckets
class_docstr_tok: ["Helper","class","to","simplify","the","handling","of","parameter","buckets"]
code: def _add_param_as_view(
      self, param: torch.Tensor, keep_existing_value: bool = True
  ) -> None:
      assert self.buffer is not None
      assert (
          param.dtype == self.buffer.dtype
      ), f"Different types for the bucket and the param, cannot proceed: {param.dtype} - {self.buffer.dtype}"
      assert (
          param.device == self.buffer.device
      ), f"Different devices for the bucket and the param, cannot proceed: {param.device} - {self.buffer.device}"
  
      fill_next = self._fill + param.numel()
      assert fill_next <= self.buffer.numel()
  
      # Copy the current param value
      if keep_existing_value:
          self.buffer[self._fill : fill_next].copy_(
              param.data.flatten()
          )
      param.data = self.buffer[self._fill : fill_next].view_as(
          param.data
      )
      self._fill = fill_next
  
imports: from typing import Any, Callable, List, Optional, Union
  import torch
label_desc: Use image node_id 4 for calling the ParamBucket obj's underlying member method code with example usage: obj._add_param_as_view(param, keep_existing_value) without return types