class_docstr: Tests for is_independent, which tests a function to be
  independent of its inputs, using Autograd.
class_docstr_tok: ["Tests","for","is_independent",",","which","tests","a","function","to","be","independent","of","its","inputs",",","using","Autograd","."]
docstr: Tests that no deprecation warning arises when using qml.grad with
  qml.math.is_independent.
docstr_tok: ["Tests","that","no","deprecation","warning","arises","when","using","qml.grad","with","qml.math.is_independent","."]
code: def test_no_trainable_params_deprecation_grad(self, recwarn):
      """Tests that no deprecation warning arises when using qml.grad with
      qml.math.is_independent.
      """
  
      def lin(x):
          return pnp.sum(x)
  
      x = pnp.array([0.2, 9.1, -3.2], requires_grad=True)
      jac = qml.grad(lin)
      assert qml.math.is_independent(jac, "autograd", (x,), {})
  
      assert len(recwarn) == 0
  
imports: import pytest
  import numpy
  from pennylane import numpy
  import pennylane
  from pennylane.math import is_independent
  from pennylane.math.is_independent import _get_random_args
label_desc: Use image node_id 6 for calling the TestIsIndependentAutograd obj's underlying member method code with example usage: obj.test_no_trainable_params_deprecation_grad(recwarn) and returns: pnp