code: def _accumulated_cost_matrix_no_region(cost_matrix):
      n_timestamps_1, n_timestamps_2 = cost_matrix.shape
      acc_cost_mat = np.empty((n_timestamps_1, n_timestamps_2))
      acc_cost_mat[0] = np.cumsum(cost_matrix[0])
      acc_cost_mat[:, 0] = np.cumsum(cost_matrix[:, 0])
      for j in range(1, n_timestamps_2):
          for i in range(1, n_timestamps_1):
              acc_cost_mat[i, j] = cost_matrix[i, j] + min(
                  acc_cost_mat[i - 1][j - 1],
                  acc_cost_mat[i - 1][j],
                  acc_cost_mat[i][j - 1],
              )
      return acc_cost_mat
  
imports: import numpy
  from math import ceil, log2, sqrt
  from numba import njit, prange
  from sklearn.utils import check_array
label_desc: Use image node_id 11 for calling a global function with example usage: _accumulated_cost_matrix_no_region(cost_matrix) and returns: acc_cost_mat