code: def compress(
      self,
      tensor: torch.Tensor,
      info: CompressionInfo,
      allow_inplace: bool = False,
  ):
      self.mp_counter.value += 1
      if info.part_size is not None:
          self.mp_part_size.value = max(
              self.mp_part_size.value, info.part_size
          )
      return self.compression.compress(
          tensor, info=info, allow_inplace=allow_inplace
      )
  
imports: import multiprocessing
  from ctypes import c_int32
  import pytest
  import torch
  import torch.nn
  import hivemind
  from hivemind.compression import CompressionBase, CompressionInfo, Float16Compression, NoCompression, PerTensorCompression, RoleAdaptiveCompression, SizeAdaptiveCompression, Uniform8BitQuantization, deserialize_torch_tensor, serialize_torch_tensor
  from hivemind.compression.adaptive import AdaptiveCompressionBase
  from hivemind.proto.runtime_pb2 import CompressionType
  from hivemind.utils.streaming import combine_from_streaming, split_for_streaming
  from test_utils.dht_swarms import launch_dht_instances
label_desc: Use image node_id 3 for calling the TrackedCompression obj's underlying member method code with example usage: obj.compress(tensor, info, allow_inplace) and returns: self