code: def test_float32(self):
      minimum = np.array([1.0, 1.0], dtype=np.float32)
      scales = np.array([2.0, 3.0], dtype=np.float32)
      start = np.zeros_like(minimum)
  
      @tff.math.make_val_and_grad_fn
      def quadratic(x):
          return tf.reduce_sum(input_tensor=scales * (x - minimum) ** 2)
  
      result = tff.math.optimizer.conjugate_gradient_minimize(
          quadratic, initial_position=start
      )
      self.assertEqual(result.position.dtype, tf.float32)
      self.assertArrayNear(
          self.evaluate(result.position), minimum, 1e-5
      )
  
imports: import numpy
  import tensorflow.compat.v2
  import tf_quant_finance
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 20 for calling the ConjugateGradientTest obj's underlying member method code with example usage: obj.test_float32() and returns: tf