code: def sl_fun_jac(x, y, p):
      n, m = y.shape
      df_dy = np.empty((n, 2, m))
      df_dy[0, 0] = 0
      df_dy[0, 1] = 1
      df_dy[1, 0] = -p[0] ** 2
      df_dy[1, 1] = 0
  
      df_dp = np.empty((n, 1, m))
      df_dp[0, 0] = 0
      df_dp[1, 0] = -2 * p[0] * y[0]
  
      return df_dy, df_dp
  
imports: import sys
  import numpy
  from numpy.testing import assert_, assert_array_equal, assert_allclose, assert_equal
  from pytest import raises
  from scipy.sparse import coo_matrix
  from scipy.special import erf
  from scipy.integrate._bvp import modify_mesh, estimate_fun_jac, estimate_bc_jac, compute_jac_indices, construct_global_jac, solve_bvp
label_desc: Use image node_id 8 for calling a global function with example usage: sl_fun_jac(x, y, p) and returns: df_dy,  df_dp