code: def sum(
      a,
      axis=None,
      dtype=None,
      out=None,
      keepdims=False,
      initial=None,
      where=None,
      promote_integers=True,
  ):
      # TODO: promote_integers is only supported from JAX v0.4.10
      if dtype is None and promote_integers:
          if ivy.is_bool_dtype(a.dtype):
              dtype = ivy.default_int_dtype()
          elif ivy.is_uint_dtype(a.dtype):
              dtype = "uint64"
              a = ivy.astype(a, dtype)
          elif ivy.is_int_dtype(a.dtype):
              dtype = "int64"
              a = ivy.astype(a, dtype)
          else:
              dtype = a.dtype
      elif dtype is None and not promote_integers:
          dtype = (
              "float32"
              if ivy.is_int_dtype(a.dtype)
              else ivy.as_ivy_dtype(a.dtype)
          )
  
      if initial:
          if axis is None:
              a = ivy.reshape(a, (1, -1))
              axis = 0
          s = list(ivy.shape(a))
          s[axis] = 1
          header = ivy.full(s, initial)
          a = ivy.concat([a, header], axis=axis)
  
      ret = ivy.sum(a, axis=axis, keepdims=keepdims, out=out)
  
      if ivy.is_array(where):
          where = ivy.array(where, dtype=ivy.bool)
          ret = ivy.where(
              where, ret, ivy.default(out, ivy.zeros_like(ret)), out=out
          )
      return ivy.astype(ret, ivy.as_ivy_dtype(dtype))
  
imports: import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.frontends.jax.func_wrapper import to_ivy_arrays_and_back, handle_jax_dtype
  from ivy.functional.frontends.jax.numpy import promote_types_of_jax_inputs
  from ivy.functional.backends.jax.experimental.elementwise import _normalize_axis_tuple
label_desc: Use image node_id 26 for calling a global function with example usage: sum(a, axis, dtype, out, keepdims, initial, where, promote_integers) and returns: ivy