code: def test_mish(self):
      # Basic test for the mish activation function
      x = np.random.random((2, 5))
      result = activations.mish(x[np.newaxis, :])[0]
      expected = x * np.tanh(_ref_softplus(x))
      self.assertAllClose(result, expected, rtol=1e-05)
  
      x = np.random.uniform(-10, 10, (2, 5))
      result = activations.mish(x[np.newaxis, :])[0]
      expected = x * np.tanh(_ref_softplus(x))
      self.assertAllClose(result, expected, rtol=1e-05)
  
      # Test with 1D array
      x_1d = np.random.uniform(-10, 10, 5)
      result_1d = activations.mish(x_1d)
      expected_1d = x_1d * np.tanh(_ref_softplus(x_1d))
      self.assertAllClose(result_1d, expected_1d, rtol=1e-05)
  
      # Test with 3D array
      x_3d = np.random.uniform(-10, 10, (3, 3, 3))
      result_3d = activations.mish(x_3d)
      expected_3d = x_3d * np.tanh(_ref_softplus(x_3d))
      self.assertAllClose(result_3d, expected_3d, rtol=1e-05)
  
      # Test with strictly positive values
      x_positive = np.random.uniform(0, 10, (2, 5))
      result_positive = activations.mish(x_positive)
      expected_positive = x_positive * np.tanh(
          _ref_softplus(x_positive)
      )
      self.assertAllClose(
          result_positive, expected_positive, rtol=1e-05
      )
  
      # Test with strictly negative values
      x_negative = np.random.uniform(-10, 0, (2, 5))
      result_negative = activations.mish(x_negative)
      expected_negative = x_negative * np.tanh(
          _ref_softplus(x_negative)
      )
      self.assertAllClose(
          result_negative, expected_negative, rtol=1e-05
      )
  
      # Test near zero values
      x_zero = np.random.uniform(-1e-7, 1e-7, (2, 5))
      result_zero = activations.mish(x_zero)
      expected_zero = x_zero * np.tanh(_ref_softplus(x_zero))
      self.assertAllClose(result_zero, expected_zero, rtol=1e-05)
  
      # Test large values to check stability
      x_large = np.random.uniform(1e4, 1e5, (2, 5))
      result_large = activations.mish(x_large)
      expected_large = x_large * np.tanh(_ref_softplus(x_large))
      self.assertAllClose(result_large, expected_large, rtol=1e-05)
  
imports: import numpy
  from keras import activations
  from keras import backend
  from keras import testing
label_desc: Use image node_id 37 for calling the ActivationsTest obj's underlying member method code with example usage: obj.test_mish() without return types