code: def test_eval_partial_derivative_single_2nd_rank_tensors_by_tensor():
      expr1 = PartialDerivative(H(i, j), H(m, m1))
      assert (
          expr1._perform_derivative() - L.delta(i, -m) * L.delta(j, -m1)
          == 0
      )
  
      expr2 = PartialDerivative(H(i, j), H(-m, m1))
      assert (
          expr2._perform_derivative()
          - L.metric(i, L_0) * L.delta(-L_0, m) * L.delta(j, -m1)
          == 0
      )
  
      expr3 = PartialDerivative(H(i, j), H(m, -m1))
      assert (
          expr3._perform_derivative()
          - L.delta(i, -m) * L.metric(j, L_0) * L.delta(-L_0, m1)
          == 0
      )
  
      expr4 = PartialDerivative(H(i, j), H(-m, -m1))
      assert (
          expr4._perform_derivative()
          - L.metric(i, L_0)
          * L.delta(-L_0, m)
          * L.metric(j, L_1)
          * L.delta(-L_1, m1)
          == 0
      )
  
imports: from sympy import sin, cos
  from sympy.testing.pytest import raises
  from sympy.tensor.toperators import PartialDerivative
  from sympy.tensor.tensor import TensorIndexType, tensor_indices, TensorHead, tensor_heads
  from sympy.core.numbers import Rational
  from sympy.core.symbol import symbols
  from sympy.matrices.dense import diag
  from sympy.tensor.array import Array
  from sympy.core.random import randint
label_desc: Use image node_id 11 for calling a global function with example usage: test_eval_partial_derivative_single_2nd_rank_tensors_by_tensor() without return types