code: def benchmark_compression(
      tensor: torch.Tensor, compression_type: CompressionType
  ) -> [float, float, int]:
      t = time.time()
      serialized = serialize_torch_tensor(tensor, compression_type)
      result = deserialize_torch_tensor(serialized)
      return (
          time.time() - t,
          (tensor - result).square().mean(),
          serialized.ByteSize(),
      )
  
imports: import argparse
  import time
  import torch
  from hivemind.compression import deserialize_torch_tensor, serialize_torch_tensor
  from hivemind.proto.runtime_pb2 import CompressionType
  from hivemind.utils.logging import get_logger, use_hivemind_log_handler
label_desc: Use image node_id 1 for calling a global function with example usage: benchmark_compression(tensor, compression_type) and returns: unknown,  unknown,  serialized