code: def test_serialize_tensor():
      tensor = torch.randn(512, 12288, requires_grad=True)
      for chunk_size in [1024, 64 * 1024, 64 * 1024 + 1, 10**9]:
          _check(tensor, CompressionType.NONE, chunk_size=chunk_size)
  
      _check(tensor, CompressionType.FLOAT16, rtol=0.0, atol=1e-2)
      _check(torch.randint(0, 100, (512, 1, 1)), CompressionType.NONE)
      _check(
          torch.randn(10, 20), CompressionType.MEANSTD_16BIT, atol=0.1
      )
      _check(torch.tensor(1.0), CompressionType.NONE)
      _check(torch.tensor(1.0), CompressionType.FLOAT16)
  
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 a global function with example usage: test_serialize_tensor() without return types