code: def align_dataframe_dataframe(left, right, axis=None):
      left_index_chunks = [c.index_value for c in left.cix[:, 0]]
      right_index_chunks = [c.index_value for c in right.cix[:, 0]]
      left_columns_chunks = [c.columns_value for c in left.cix[0, :]]
      right_columns_chunks = [c.columns_value for c in right.cix[0, :]]
  
      axis = validate_axis(axis) if axis is not None else None
      if axis is None or axis == 0:
          index_splits, index_chunk_shape = _calc_axis_splits(
              left.index_value,
              right.index_value,
              left_index_chunks,
              right_index_chunks,
          )
      else:
          index_splits, index_chunk_shape = None, None
  
      if axis is None or axis == 1:
          columns_splits, column_chunk_shape = _calc_axis_splits(
              left.columns_value,
              right.columns_value,
              left_columns_chunks,
              right_columns_chunks,
          )
      else:
          columns_splits, column_chunk_shape = None, None
  
      splits = _MinMaxSplitInfo(index_splits, columns_splits)
      out_left_chunk_shape = (
          len(
              index_chunk_shape
              or list(itertools.chain(*index_splits._left_split))
          )
          if index_splits is not None
          else left.chunk_shape[0],
          len(
              column_chunk_shape
              or list(itertools.chain(*columns_splits._left_split))
          )
          if columns_splits is not None
          else left.chunk_shape[1],
      )
      if axis is None:
          out_right_chunk_shape = out_left_chunk_shape
      else:
          out_right_chunk_shape = (
              len(
                  index_chunk_shape
                  or list(itertools.chain(*index_splits._right_split))
              )
              if index_splits is not None
              else right.chunk_shape[0],
              len(
                  column_chunk_shape
                  or list(itertools.chain(*columns_splits._right_split))
              )
              if columns_splits is not None
              else right.chunk_shape[1],
          )
      left_chunks = _gen_dataframe_chunks(
          splits, out_left_chunk_shape, 0, left
      )
      right_chunks = _gen_dataframe_chunks(
          splits, out_right_chunk_shape, 1, right
      )
  
      index_nsplits = columns_nsplits = None
      if axis is None or axis == 0:
          if _is_index_identical(left_index_chunks, right_index_chunks):
              index_nsplits = left.nsplits[0]
          else:
              index_nsplits = [
                  np.nan for _ in range(out_left_chunk_shape[0])
              ]
      if axis is None or axis == 1:
          if _is_index_identical(
              left_columns_chunks, right_columns_chunks
          ):
              columns_nsplits = left.nsplits[1]
          else:
              columns_nsplits = [
                  np.nan for _ in range(out_left_chunk_shape[1])
              ]
  
      nsplits = [index_nsplits, columns_nsplits]
  
      out_chunk_shapes = (out_left_chunk_shape, out_right_chunk_shape)
      return nsplits, out_chunk_shapes, left_chunks, right_chunks
  
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 10 for calling a global function with example usage: align_dataframe_dataframe(left, right, axis) and returns: nsplits,  out_chunk_shapes,  left_chunks,  right_chunks