code: def _eq_ragged_ragged(
      start_indices1, flat_array1, start_indices2, flat_array2
  ):
      """
      Compare elements of two ragged arrays of the same length
  
      Parameters
      ----------
      start_indices1: ndarray
          start indices of a RaggedArray 1
      flat_array1: ndarray
          flat_array property of a RaggedArray 1
      start_indices2: ndarray
          start indices of a RaggedArray 2
      flat_array2: ndarray
          flat_array property of a RaggedArray 2
  
      Returns
      -------
      mask: ndarray
          1D bool array of same length as inputs with elements True when
          corresponding elements are equal, False otherwise
      """
      n = len(start_indices1)
      m1 = len(flat_array1)
      m2 = len(flat_array2)
  
      result = np.zeros(n, dtype=np.bool_)
  
      for i in range(n):
          # Extract inds for ra1
          start_index1 = start_indices1[i]
          stop_index1 = start_indices1[i + 1] if i < n - 1 else m1
          len_1 = stop_index1 - start_index1
  
          # Extract inds for ra2
          start_index2 = start_indices2[i]
          stop_index2 = start_indices2[i + 1] if i < n - 1 else m2
          len_2 = stop_index2 - start_index2
  
          if len_1 != len_2:
              el_equal = False
          else:
              el_equal = True
              for flat_index1, flat_index2 in zip(
                  range(start_index1, stop_index1),
                  range(start_index2, stop_index2),
              ):
                  el_1 = flat_array1[flat_index1]
                  el_2 = flat_array2[flat_index2]
                  el_equal &= el_1 == el_2
  
          result[i] = el_equal
  
      return result
  
imports: from __future__ import annotations
  import re
  from functools import total_ordering
  from packaging.version import Version
  import numpy
  import pandas
  from numba import jit
  from pandas.api.extensions import ExtensionDtype, ExtensionArray, register_extension_dtype
  from numbers import Integral
  from pandas.api.types import pandas_dtype, is_extension_array_dtype
label_desc: Use image node_id 3 for calling a global function with example usage: _eq_ragged_ragged(start_indices1, flat_array1, start_indices2, flat_array2) and returns: result