code: def index_copy(input, dim, index, source, *, out=None):
      input = ivy.swapaxes(input, dim, 0)
      source = ivy.swapaxes(source, dim, 0)
      index = sorted(
          zip(ivy.to_list(index), range(len(index))),
          key=(lambda x: x[0]),
      )
      res = []
      while index:
          _curr_idx = index[0][0]
          for i in range(len(res), _curr_idx):
              res.append(ivy.get_item(input, i))
          while (len(index) > 1) and (index[0][0] == index[1][0]):
              index.pop(0)
          res.append(ivy.get_item(source, index[0][1]))
          index.pop(0)
      for i in range(len(res), input.shape[0]):
          res.append(ivy.get_item(input, i))
      res = ivy.stack(res)
      if len(input.shape) < 2:
          res = ivy.flatten(res)
  
      return ivy.swapaxes(res, 0, dim, out=out)
  
imports: import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back, numpy_to_torch_style_args, to_ivy_shape
  import ivy.functional.frontends.torch
label_desc: Use image node_id 15 for calling a global function with example usage: index_copy(input, dim, index, source) and returns: ivy