code: def test_pad_across_processes(state):
      # We need to pad the tensor with one more element if we are the main process
      # to ensure that we can pad
      if state.is_main_process:
          tensor = torch.arange(state.num_processes + 1).to(
              state.device
          )
      else:
          tensor = torch.arange(state.num_processes).to(state.device)
      padded_tensor = pad_across_processes(tensor)
      assert padded_tensor.shape == torch.Size(
          [state.num_processes + 1]
      )
      if not state.is_main_process:
          assert padded_tensor.tolist() == list(
              range(0, state.num_processes)
          ) + [0]
  
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 6 for calling a global function with example usage: test_pad_across_processes(state) without return types