code: def pack_decode_float_tensor(
      self,
      tensor: "PHETensorEncoded",
      offset_bit: int,
      pack_num: int,
      precision: int,
  ):
      from ._tensor import PHETensorEncoded
  
      if isinstance(tensor, PHETensorEncoded):
          return self._coder.unpack_floats(
              tensor.data,
              offset_bit,
              pack_num,
              precision,
              tensor.shape.numel(),
          )
      elif hasattr(tensor, "pack_decode_float_tensor"):
          return tensor.pack_decode_float_tensor(
              self, offset_bit, pack_num, precision
          )
      else:
          raise NotImplementedError(f"`{tensor}` not supported")
  
imports: import typing
  import torch
label_desc: Use image node_id 5 for calling the PHETensorCoder obj's underlying member method code with example usage: obj.pack_decode_float_tensor(tensor, offset_bit, pack_num, precision) and returns: self, tensor