code: def get_num_ways_dim_sharded(
      hlo_sharding: xc.HloSharding,
  ) -> tuple[Sequence[int], int]:
      if hlo_sharding.is_replicated():  # type: ignore
          return [], 1
      partitions = hlo_sharding.tile_assignment_dimensions()
      subgroup_types = hlo_sharding.subgroup_types()
  
      if subgroup_types == [xc.OpSharding.Type.REPLICATED]:
          replicate_on_last_tile_dim = True
      else:
          replicate_on_last_tile_dim = (
              hlo_sharding.replicate_on_last_tile_dim()
          )
          if subgroup_types:
              raise NotImplementedError(
                  "Unhandled OpSharding type. Please open a bug report!"
              )
      num_replicas = 1
      if replicate_on_last_tile_dim:
          num_replicas = partitions[-1]
          partitions = partitions[:-1]
      return partitions, num_replicas
  
file_path: jax/jax/_src/op_shardings.py
imports: from __future__ import annotations
  from collections.abc import Sequence
  import itertools
  from typing import Union
  import numpy
  from jax._src.lib import xla_client
label_desc: Use image node_id 1 for calling a global function with example usage: get_num_ways_dim_sharded(hlo_sharding) and returns: partitions,  num_replicas, list,  int