code: def test_silu(self):
      silu_vectorized = np.vectorize(_ref_silu)
  
      # Test positive values
      positive_values = np.random.uniform(0, 5.9, (2, 5))
      result = activations.silu(positive_values[np.newaxis, :])[0]
      expected = silu_vectorized(positive_values)
      self.assertAllClose(result, expected, rtol=1e-05)
  
      # Test values around zero (to ensure sigmoid behaves correctly)
      around_zero_values = np.random.uniform(-1, 1, (2, 5))
      result = activations.silu(around_zero_values[np.newaxis, :])[0]
      expected = silu_vectorized(around_zero_values)
      self.assertAllClose(result, expected, rtol=1e-05)
  
      # Test negative values
      negative_values = np.random.uniform(-5.9, 0, (2, 5))
      result = activations.silu(negative_values[np.newaxis, :])[0]
      expected = silu_vectorized(negative_values)
      self.assertAllClose(result, expected, rtol=1e-05)
  
imports: import numpy
  from keras import activations
  from keras import backend
  from keras import testing
label_desc: Use image node_id 32 for calling the ActivationsTest obj's underlying member method code with example usage: obj.test_silu() without return types