code: def extract(
      self, serialized_tensor: runtime_pb2.Tensor
  ) -> torch.Tensor:
      original_dtype = np.dtype(serialized_tensor.dtype)
      array = np.frombuffer(serialized_tensor.buffer, dtype=np.float16)
      return (
          torch.as_tensor(np.asarray(array, dtype=original_dtype))
          .reshape(tuple(serialized_tensor.size))
          .requires_grad_(serialized_tensor.requires_grad)
      )
  
file_path: hivemind/hivemind/compression/floating.py
imports: import math
  import numpy
  import torch
  from hivemind.compression.base import CompressionBase, CompressionInfo
  from hivemind.proto import runtime_pb2
label_desc: Use image node_id 2 for calling the Float16Compression obj's underlying member method code with example usage: obj.extract(serialized_tensor) and returns: torch