code: def make_params():
      return [
          nn.Parameter(x)
          for x in (
              torch.randn([]),
              torch.randn(1),
              torch.randn(100),
              torch.randn(1_000),
              torch.randn(5_000),
              torch.randn(10_000),
          )
      ]
  
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 7 for calling a global function with example usage: make_params() and returns: unknown