code: def build_reduce_chunk_kw(self, inputs, index, **kw):
      kw["index"] = index
      if (
          kw.get("index_value", None) is None
          and inputs[0].inputs[0].index_value is not None
      ):
          index_align_map_chunks = inputs[0].inputs
          if index_align_map_chunks[0].op.index_min_max is not None:
              # shuffle on columns, all the DataFrameIndexAlignMap has the same index
              kw["index_value"] = filter_index_value(
                  index_align_map_chunks[0].index_value,
                  index_align_map_chunks[0].op.index_min_max,
              )
          else:
              # shuffle on index
              kw["index_value"] = parse_index(
                  index_align_map_chunks[0].index_value.to_pandas(),
                  [c.key for c in index_align_map_chunks],
                  type(self).__name__,
              )
      if self.output_types[0] == OutputType.dataframe:
          if (
              kw.get("columns_value", None) is None
              and getattr(inputs[0].inputs[0], "columns_value", None)
              is not None
          ):
              index_align_map_chunks = inputs[0].inputs
              if (
                  index_align_map_chunks[0].op.column_min_max
                  is not None
              ):
                  # shuffle on index
                  kw["columns_value"] = filter_index_value(
                      index_align_map_chunks[0].columns_value,
                      index_align_map_chunks[0].op.column_min_max,
                      store_data=True,
                  )
                  kw["dtypes"] = index_align_map_chunks[0].dtypes[
                      kw["columns_value"].to_pandas()
                  ]
              else:
                  # shuffle on columns
                  all_dtypes = [
                      c.op.column_shuffle_segments[index[1]]
                      for c in index_align_map_chunks
                      if c.index[0]
                      == index_align_map_chunks[0].index[0]
                  ]
                  kw["dtypes"] = pd.concat(all_dtypes)
                  kw["columns_value"] = parse_index(
                      kw["dtypes"].index, store_data=True
                  )
      else:
          if (
              kw.get("dtype", None) is None
              and getattr(inputs[0].inputs[0], "dtype", None)
              is not None
          ):
              kw["dtype"] = inputs[0].inputs[0].dtype
          if (
              kw.get("name", None) is None
              and getattr(inputs[0].inputs[0], "name", None) is not None
          ):
              kw["name"] = inputs[0].inputs[0].name
      return kw
  
imports: import itertools
  import operator
  import numpy
  import pandas
  from ..None import opcodes
  from ..core import OutputType
  from ..core.operand import OperandStage, MapReduceOperand
  from ..serialization.serializables import FieldTypes, AnyField, BoolField, Int32Field, KeyField, ListField
  from .core import SERIES_CHUNK_TYPE
  from .utils import hash_dtypes, filter_dtypes
  from .operands import DataFrameOperandMixin, DataFrameShuffleProxy
  from .utils import parse_index, split_monotonic_index_min_max, build_split_idx_to_origin_idx, filter_index_value, hash_index, is_index_value_identical, validate_axis
label_desc: Use image node_id 6 for calling the DataFrameIndexAlign obj's underlying member method code with example usage: obj.build_reduce_chunk_kw(inputs, index) and returns: kw