code: def __post_init__(self):
      if not self.validate:
          return
      if len(self.indices) != len(self.shape):
          raise ValueError(
              f"`indices` must be the same length as `Ref` shape.: {self}."
          )
      # We validate integer indexing shapes here
      for idx, s in zip(self.indices, self.shape):
          if isinstance(idx, Slice):
              start = idx.start
              if value := _maybe_concretize(start):
                  if value >= s:
                      raise ValueError(
                          f"Out of bound slice: start={value}, dim={s}."
                      )
                  if value + idx.size > s:
                      raise ValueError(
                          f"Out of bound slice: start={value}, size={idx.size}, dim={s}."
                      )
              continue
          # The shape of indexer integers should be broadcastable up to the
          # int_indexer_shape of the whole NDIndexer
          if not np.shape(idx):
              if (value := _maybe_concretize(idx)) and value >= s:
                  raise ValueError(
                      f"Out of bound indexer: idx={value}, dim={s}."
                  )
              # For ()-shaped indexers, we can broadcast no problm.
              continue
          # If we don't have a ()-shaped indexer, the rank must match
          # int_indexer_shape
          if np.ndim(idx) != len(self.int_indexer_shape):
              raise ValueError(
                  f"Indexer must have rank {np.ndim(idx)}: {idx=} vs."
                  f" {self.int_indexer_shape=}"
              )
          # Here we check that the shapes broadcast.
          try:
              np.broadcast_shapes(np.shape(idx), self.int_indexer_shape)
          except ValueError as e:
              raise ValueError(
                  f"Could not broadcast integer indexer: {idx=} vs."
                  f" {self.int_indexer_shape=}"
              ) from e
  
imports: from __future__ import annotations
  import dataclasses
  from typing import Any, Union
  from jax._src import core
  from jax._src import tree_util
  from jax._src.typing import Array
  from jax._src.util import merge_lists
  from jax._src.util import partition_list
  import numpy
label_desc: Use image node_id 1 for calling the NDIndexer obj's underlying member method code with example usage: obj.__post_init__() without return types