code: def test_eval_partial_derivative_mixed_scalar_tensor_expr2():
      tau, alpha = symbols("tau alpha")
  
      base_expr2 = A(i) * A(-i) + tau**2
  
      vector_expression = PartialDerivative(
          base_expr2, A(k)
      )._perform_derivative()
      assert (
          vector_expression
          - (
              L.delta(L_0, -k) * A(-L_0)
              + A(L_0) * L.metric(-L_0, -L_1) * L.delta(L_1, -k)
          )
      ).expand() == 0
  
      scalar_expression = PartialDerivative(
          base_expr2, tau
      )._perform_derivative()
      assert scalar_expression == 2 * tau
  
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 14 for calling a global function with example usage: test_eval_partial_derivative_mixed_scalar_tensor_expr2() without return types