code: def __getitem__(self, key):
      if not isinstance(key, tuple):
          key = (key,)
  
      # copy attributes, since they can be overridden in the first argument
      trans1d = self.trans1d
      ndmin = self.ndmin
      matrix = self.matrix
      axis = self.axis
  
      objs = []
      # dtypes or scalars for weak scalar handling in result_type
      result_type_objs = []
  
      for k, item in enumerate(key):
          scalar = False
          if isinstance(item, slice):
              step = item.step
              start = item.start
              stop = item.stop
              if start is None:
                  start = 0
              if step is None:
                  step = 1
              if ivy.is_complex_dtype(step):
                  size = int(abs(step))
                  newobj = np_frontend.linspace(
                      start, stop, num=size
                  ).ivy_array
              else:
                  newobj = np_frontend.arange(
                      start, stop, step
                  ).ivy_array
              if ndmin > 1:
                  newobj = np_frontend.array(
                      newobj, copy=False, ndmin=ndmin
                  ).ivy_array
                  if trans1d != -1:
                      newobj = ivy.swapaxes(newobj, -1, trans1d)
          elif isinstance(item, str):
              if k != 0:
                  raise ValueError(
                      "special directives must be the first entry."
                  )
              if item in ("r", "c"):
                  matrix = True
                  col = item == "c"
                  continue
              if "," in item:
                  vec = item.split(",")
                  try:
                      axis, ndmin = (int(x) for x in vec[:2])
                      if len(vec) == 3:
                          trans1d = int(vec[2])
                      continue
                  except Exception as e:
                      raise ValueError(
                          f"unknown special directive {item!r}"
                      ) from e
              try:
                  axis = int(item)
                  continue
              except (ValueError, TypeError) as e:
                  raise ValueError("unknown special directive") from e
          elif (ivy.isscalar(item)) or (
              ivy.is_ivy_array(item) and item.ndim == 0
          ):
              scalar = True
              newobj = item
          else:
              item = ivy.array(item)
              newobj = np_frontend.array(
                  item, copy=False, ndmin=ndmin
              ).ivy_array
              if trans1d != -1 and item.ndim < ndmin:
                  k2 = ndmin - item.ndim
                  k1 = trans1d
                  if k1 < 0:
                      k1 += k2 + 1
                  defaxes = list(range(ndmin))
                  axes = defaxes[:k1] + defaxes[k2:] + defaxes[k1:k2]
                  newobj = np_frontend.transpose(
                      newobj, axes=axes
                  ).ivy_array
  
          objs.append(newobj)
          if scalar:
              result_type_objs.append(item)
          else:
              result_type_objs.append(newobj.dtype)
  
      # Ensure that scalars won't up-cast unless warranted, for 0, drops
      # through to error in concatenate.
      if len(result_type_objs) != 0:
          if len(result_type_objs) > 1:
              final_dtype = ivy.result_type(*result_type_objs)
          else:
              final_dtype = ivy.result_type(
                  result_type_objs[0], result_type_objs[0]
              )
          # concatenate could do cast, but that can be overridden:
          objs = [
              np_frontend.array(
                  obj, copy=False, ndmin=ndmin, dtype=final_dtype
              ).ivy_array
              for obj in objs
          ]
  
      res = self.concatenate(tuple(objs), axis=axis)
  
      if matrix:
          oldndim = res.ndim
          res = self.makemat(res)
          if oldndim == 1 and col:
              res = res.T
      return res
  
file_path: ivy/ivy/functional/frontends/numpy/indexing_routines/inserting_data_into_arrays.py
imports: import ivy
  from ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back
  import ivy.functional.frontends.numpy
label_desc: Use image node_id 2 for calling the AxisConcatenator obj's underlying member method code with example usage: obj.__getitem__(key) and returns: res