code: def test_torch_index_add(
      *,
      xs_dtypes_dim_idx,
      alpha,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      xs, input_dtypes, axis, indices = xs_dtypes_dim_idx
      if xs[0].shape[axis] < xs[1].shape[axis]:
          source, input = xs
      else:
          input, source = xs
      helpers.test_frontend_function(
          input_dtypes=[input_dtypes[0], "int64", input_dtypes[1]],
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          rtol=1e-03,
          input=input,
          dim=axis,
          index=indices,
          source=source,
          alpha=alpha,
      )
  
imports: import random
  from hypothesis import strategies
  import math
  import ivy
  import ivy_tests.test_ivy.helpers
  import ivy_tests.test_ivy.helpers.globals
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_core.test_manipulation import _get_splits
  from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import two_broadcastable_shapes
label_desc: Use image node_id 25 for calling a global function with example usage: test_torch_index_add() without return types