code: def test_broadcast_data():
      Utils.initialize_model_parallel(2, 4)
      input_data = {
          0: torch.ones((8, 8)).cuda() * 0.0,
          1: torch.ones((8, 8)).cuda() * 1.0,
          2: torch.ones((8, 8)).cuda() * 2.0,
          3: torch.ones((8, 8)).cuda() * 3.0,
          4: torch.ones((8, 8)).cuda() * 4.0,
          5: torch.ones((8, 8)).cuda() * 5.0,
          6: torch.ones((8, 8)).cuda() * 6.0,
          7: torch.ones((8, 8)).cuda() * 7.0,
      }
      dtype = torch.float32
      actual_output = broadcast_data([0, 1], input_data, dtype)
      assert torch.equal(actual_output[0], input_data[0])
      assert torch.equal(actual_output[1], input_data[1])
      Utils.destroy_model_parallel()
  
imports: from megatron.core.tensor_parallel.data import broadcast_data
  import torch
  from tests.unit_tests.test_utilities import Utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_broadcast_data() without return types