code: def test_broadcast(state):
      tensor = create_tensor(state)
      broadcasted_tensor = broadcast(tensor)
      assert broadcasted_tensor.shape == torch.Size(
          [state.num_processes]
      )
      assert broadcasted_tensor.tolist() == list(
          range(1, state.num_processes + 1)
      )
  
file_path: accelerate/src/accelerate/test_utils/scripts/test_ops.py
imports: import torch
  from accelerate import PartialState
  from accelerate.test_utils.testing import assert_exception
  from accelerate.utils.dataclasses import DistributedType
  from accelerate.utils.operations import DistributedOperationException, broadcast, gather, gather_object, pad_across_processes, reduce
label_desc: Use image node_id 5 for calling a global function with example usage: test_broadcast(state) without return types